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Math.NET Numerics: 4.9.0 api update

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Christoph Ruegg 7 years ago
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  1. 2
      api/MathNet.Numerics.Differentiation/FiniteDifferenceCoefficients.htm
  2. 2
      api/MathNet.Numerics.Differentiation/NumericalDerivative.htm
  3. 2
      api/MathNet.Numerics.Differentiation/NumericalHessian.htm
  4. 2
      api/MathNet.Numerics.Differentiation/NumericalJacobian.htm
  5. 12
      api/MathNet.Numerics.Differentiation/StepType.htm
  6. 2
      api/MathNet.Numerics.Differentiation/index.htm
  7. 11
      api/MathNet.Numerics.Distributions/Bernoulli.htm
  8. 11
      api/MathNet.Numerics.Distributions/Beta.htm
  9. 11
      api/MathNet.Numerics.Distributions/BetaScaled.htm
  10. 11
      api/MathNet.Numerics.Distributions/Binomial.htm
  11. 774
      api/MathNet.Numerics.Distributions/Burr.htm
  12. 11
      api/MathNet.Numerics.Distributions/Categorical.htm
  13. 11
      api/MathNet.Numerics.Distributions/Cauchy.htm
  14. 11
      api/MathNet.Numerics.Distributions/Chi.htm
  15. 11
      api/MathNet.Numerics.Distributions/ChiSquared.htm
  16. 11
      api/MathNet.Numerics.Distributions/ContinuousUniform.htm
  17. 11
      api/MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm
  18. 11
      api/MathNet.Numerics.Distributions/Dirichlet.htm
  19. 11
      api/MathNet.Numerics.Distributions/DiscreteUniform.htm
  20. 11
      api/MathNet.Numerics.Distributions/Erlang.htm
  21. 11
      api/MathNet.Numerics.Distributions/Exponential.htm
  22. 11
      api/MathNet.Numerics.Distributions/FisherSnedecor.htm
  23. 11
      api/MathNet.Numerics.Distributions/Gamma.htm
  24. 11
      api/MathNet.Numerics.Distributions/Geometric.htm
  25. 11
      api/MathNet.Numerics.Distributions/Hypergeometric.htm
  26. 11
      api/MathNet.Numerics.Distributions/IContinuousDistribution.htm
  27. 11
      api/MathNet.Numerics.Distributions/IDiscreteDistribution.htm
  28. 11
      api/MathNet.Numerics.Distributions/IDistribution.htm
  29. 11
      api/MathNet.Numerics.Distributions/IUnivariateDistribution.htm
  30. 11
      api/MathNet.Numerics.Distributions/InverseGamma.htm
  31. 807
      api/MathNet.Numerics.Distributions/InverseGaussian.htm
  32. 11
      api/MathNet.Numerics.Distributions/InverseWishart.htm
  33. 11
      api/MathNet.Numerics.Distributions/Laplace.htm
  34. 11
      api/MathNet.Numerics.Distributions/LogNormal.htm
  35. 11
      api/MathNet.Numerics.Distributions/MatrixNormal.htm
  36. 11
      api/MathNet.Numerics.Distributions/MeanPrecisionPair.htm
  37. 11
      api/MathNet.Numerics.Distributions/Multinomial.htm
  38. 11
      api/MathNet.Numerics.Distributions/NegativeBinomial.htm
  39. 11
      api/MathNet.Numerics.Distributions/Normal.htm
  40. 11
      api/MathNet.Numerics.Distributions/NormalGamma.htm
  41. 11
      api/MathNet.Numerics.Distributions/Pareto.htm
  42. 11
      api/MathNet.Numerics.Distributions/Poisson.htm
  43. 11
      api/MathNet.Numerics.Distributions/Rayleigh.htm
  44. 11
      api/MathNet.Numerics.Distributions/Stable.htm
  45. 11
      api/MathNet.Numerics.Distributions/StudentT.htm
  46. 11
      api/MathNet.Numerics.Distributions/Triangular.htm
  47. 822
      api/MathNet.Numerics.Distributions/TruncatedPareto.htm
  48. 11
      api/MathNet.Numerics.Distributions/Weibull.htm
  49. 11
      api/MathNet.Numerics.Distributions/Wishart.htm
  50. 11
      api/MathNet.Numerics.Distributions/Zipf.htm
  51. 14
      api/MathNet.Numerics.Distributions/index.htm
  52. 2
      api/MathNet.Numerics.Financial/AbsoluteReturnMeasures.htm
  53. 2
      api/MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm
  54. 2
      api/MathNet.Numerics.Financial/index.htm
  55. 116
      api/MathNet.Numerics.IntegralTransforms/Fourier.htm
  56. 12
      api/MathNet.Numerics.IntegralTransforms/FourierOptions.htm
  57. 2
      api/MathNet.Numerics.IntegralTransforms/Hartley.htm
  58. 12
      api/MathNet.Numerics.IntegralTransforms/HartleyOptions.htm
  59. 2
      api/MathNet.Numerics.IntegralTransforms/index.htm
  60. 32
      api/MathNet.Numerics.Integration/DoubleExponentialTransformation.htm
  61. 287
      api/MathNet.Numerics.Integration/GaussKronrodRule.htm
  62. 32
      api/MathNet.Numerics.Integration/GaussLegendreRule.htm
  63. 117
      api/MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm
  64. 5
      api/MathNet.Numerics.Integration/SimpsonRule.htm
  65. 6
      api/MathNet.Numerics.Integration/index.htm
  66. 2
      api/MathNet.Numerics.Interpolation/Barycentric.htm
  67. 2
      api/MathNet.Numerics.Interpolation/BulirschStoerRationalInterpolation.htm
  68. 2
      api/MathNet.Numerics.Interpolation/CubicSpline.htm
  69. 2
      api/MathNet.Numerics.Interpolation/IInterpolation.htm
  70. 2
      api/MathNet.Numerics.Interpolation/LinearSpline.htm
  71. 2
      api/MathNet.Numerics.Interpolation/LogLinear.htm
  72. 2
      api/MathNet.Numerics.Interpolation/NevillePolynomialInterpolation.htm
  73. 2
      api/MathNet.Numerics.Interpolation/QuadraticSpline.htm
  74. 12
      api/MathNet.Numerics.Interpolation/SplineBoundaryCondition.htm
  75. 2
      api/MathNet.Numerics.Interpolation/StepInterpolation.htm
  76. 2
      api/MathNet.Numerics.Interpolation/TransformedInterpolation.htm
  77. 2
      api/MathNet.Numerics.Interpolation/index.htm
  78. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/BiCgStab.htm
  79. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/CompositeSolver.htm
  80. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/DiagonalPreconditioner.htm
  81. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/GpBiCg.htm
  82. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILU0Preconditioner.htm
  83. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILUTPPreconditioner.htm
  84. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MILU0Preconditioner.htm
  85. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MlkBiCgStab.htm
  86. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/TFQMR.htm
  87. 2
      api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/index.htm
  88. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/DenseMatrix.htm
  89. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/DenseVector.htm
  90. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/DiagonalMatrix.htm
  91. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/Matrix.htm
  92. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/SparseMatrix.htm
  93. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/SparseVector.htm
  94. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/Vector.htm
  95. 2
      api/MathNet.Numerics.LinearAlgebra.Complex/index.htm
  96. 2
      api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/BiCgStab.htm
  97. 2
      api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/CompositeSolver.htm
  98. 2
      api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/DiagonalPreconditioner.htm
  99. 2
      api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/GpBiCg.htm
  100. 2
      api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILU0Preconditioner.htm

2
api/MathNet.Numerics.Differentiation/FiniteDifferenceCoefficients.htm
View File

@ -286,7 +286,7 @@
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

2
api/MathNet.Numerics.Differentiation/NumericalDerivative.htm
View File

@ -540,7 +540,7 @@ h is approximately equal to the square-root of machine accuracy, epsilon.
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

2
api/MathNet.Numerics.Differentiation/NumericalHessian.htm
View File

@ -314,7 +314,7 @@ The function mirrors the Hessian along the diagonal since d2f/dxdy = d2f/dydx fo
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

2
api/MathNet.Numerics.Differentiation/NumericalJacobian.htm
View File

@ -363,7 +363,7 @@ added efficiency. This method also assumes that the length of vector x consisten
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

12
api/MathNet.Numerics.Differentiation/StepType.htm
View File

@ -261,8 +261,11 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -270,11 +273,8 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -338,7 +338,7 @@ input parameter. Although implementation may vary, an example of second order ac
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

2
api/MathNet.Numerics.Differentiation/index.htm
View File

@ -159,7 +159,7 @@
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

11
api/MathNet.Numerics.Distributions/Bernoulli.htm
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@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -782,7 +791,7 @@ p specifies the probability that a 1 is generated..
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

11
api/MathNet.Numerics.Distributions/Beta.htm
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@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -864,7 +873,7 @@ at the given probability. This is also known as the quantile or percent point fu
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

11
api/MathNet.Numerics.Distributions/BetaScaled.htm
View File

@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -948,7 +957,7 @@ at the given probability. This is also known as the quantile or percent point fu
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

11
api/MathNet.Numerics.Distributions/Binomial.htm
View File

@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm" class="current">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -814,7 +823,7 @@ For details about this distribution, see. <blockquote class="remarks">
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<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
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</body>

774
api/MathNet.Numerics.Distributions/Burr.htm
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@ -0,0 +1,774 @@
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Frameset//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-frameset.dtd">
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<a href="../MathNet.Numerics.Providers.LinearAlgebra/index.htm">MathNet.Numerics.Providers.LinearAlgebra</a>
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<li>
<a href="../MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/index.htm">MathNet.Numerics.Providers.LinearAlgebra.OpenBlas</a>
</li>
<li>
<a href="../MathNet.Numerics.Random/index.htm">MathNet.Numerics.Random</a>
</li>
<li>
<a href="../MathNet.Numerics.RootFinding/index.htm">MathNet.Numerics.RootFinding</a>
</li>
<li>
<a href="../MathNet.Numerics.Statistics/index.htm">MathNet.Numerics.Statistics</a>
</li>
<li>
<a href="../MathNet.Numerics.Statistics.Mcmc/index.htm">MathNet.Numerics.Statistics.Mcmc</a>
</li>
</ul>
</div>
</div><div id="types">
<h2 class="fixed">Types in MathNet.Numerics.Distributions</h2>
<div class="scroll">
<ul>
<li>
<a href="../MathNet.Numerics.Distributions/Bernoulli.htm">Bernoulli</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Beta.htm">Beta</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/BetaScaled.htm">BetaScaled</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm" class="current">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Cauchy.htm">Cauchy</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Chi.htm">Chi</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/ChiSquared.htm">ChiSquared</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/ContinuousUniform.htm">ContinuousUniform</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm">ConwayMaxwellPoisson</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Dirichlet.htm">Dirichlet</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/DiscreteUniform.htm">DiscreteUniform</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Erlang.htm">Erlang</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Exponential.htm">Exponential</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/FisherSnedecor.htm">FisherSnedecor</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Gamma.htm">Gamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Geometric.htm">Geometric</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Hypergeometric.htm">Hypergeometric</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/IContinuousDistribution.htm">IContinuousDistribution</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/IDiscreteDistribution.htm">IDiscreteDistribution</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/IDistribution.htm">IDistribution</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/IUnivariateDistribution.htm">IUnivariateDistribution</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Laplace.htm">Laplace</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/LogNormal.htm">LogNormal</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/MatrixNormal.htm">MatrixNormal</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/MeanPrecisionPair.htm">MeanPrecisionPair</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Multinomial.htm">Multinomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/NegativeBinomial.htm">NegativeBinomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Normal.htm">Normal</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/NormalGamma.htm">NormalGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Pareto.htm">Pareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Poisson.htm">Poisson</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Rayleigh.htm">Rayleigh</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Stable.htm">Stable</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/StudentT.htm">StudentT</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Wishart.htm">Wishart</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Zipf.htm">Zipf</a>
</li>
</ul>
</div>
</div>
<div class="header">
<p class="class"><strong>Type</strong> Burr</p>
<p><strong>Namespace</strong> MathNet.Numerics.Distributions</p>
<p><strong>Interfaces</strong> <a href="../MathNet.Numerics.Distributions/IContinuousDistribution.htm">IContinuousDistribution</a></p>
</div>
<div class="sub-header">
<h3 class="section">Constructors</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#.ctor">Burr</a></li>
</ul>
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#CDF">CDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#IsValidParameterSet">IsValidParameterSet</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#PDF">PDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#PDFLn">PDFLn</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Sample">Sample</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Samples">Samples</a></li>
</ul>
<h3 class="section">Methods</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#CumulativeDistribution">CumulativeDistribution</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Density">Density</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#DensityLn">DensityLn</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Equals">Equals</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#GetHashCode">GetHashCode</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#GetMoment">GetMoment</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#GetType">GetType</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Sample">Sample</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#ToString">ToString</a></li>
</ul>
<h3 class="section">Properties</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#a">a</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#c">c</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Entropy">Entropy</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#k">k</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Maximum">Maximum</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Mean">Mean</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Median">Median</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Minimum">Minimum</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Mode">Mode</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#RandomSource">RandomSource</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Skewness">Skewness</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#StdDev">StdDev</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm#Variance">Variance</a></li>
</ul>
</div>
<h3 class="section">Public Constructors</h3>
<div id=".ctor" class="method">
<h4> <strong>Burr</strong>(<span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k, <span title="System.Random">Random</span> randomSource)</h4>
<div class="content">Initializes a new instance of the Burr Type XII class.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
<p class="comments">The random number generator which is used to draw random samples. Optional, can be null. </p>
</div>
</div>
</div>
<h3 class="section">Public Static Functions</h3>
<div id="CDF" class="method">
<h4><span title="System.double">double</span> <strong>CDF</strong>(<span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the cumulative distribution at location <var>x</var>. </p>
</div>
</div>
</div>
<div id="IsValidParameterSet" class="method">
<h4><span title="System.bool">bool</span> <strong>IsValidParameterSet</strong>(<span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k)</h4>
<div class="content">Tests whether the provided values are valid parameters for this distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
</div>
</div>
</div>
<div id="PDF" class="method">
<h4><span title="System.double">double</span> <strong>PDF</strong>(<span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="PDFLn" class="method">
<h4><span title="System.double">double</span> <strong>PDFLn</strong>(<span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the log density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the log density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="Sample" class="method">
<h4><span title="System.double">double</span> <strong>Sample</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k)</h4>
<div class="content">Generates a sample from the Burr distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>a sample from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.Double[]">Double[]</span> values, <span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k)</h4>
<div class="content">Fills an array with samples generated from the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
<p class="comments">The array to fill with the samples. </p>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> a, <span title="System.double">double</span> c, <span title="System.double">double</span> k)</h4>
<div class="content">Generates a sequence of samples from the Burr distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.double">double</span></code> a</h6>
<p class="comments">The scale parameter a of the Burr distribution. Range: a > 0. </p>
<h6><code><span title="System.double">double</span></code> c</h6>
<p class="comments">The first shape parameter c of the Burr distribution. Range: c > 0. </p>
<h6><code><span title="System.double">double</span></code> k</h6>
<p class="comments">The second shape parameter k of the Burr distribution. Range: k > 0. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code></h6>
<p>a sequence of samples from the distribution. </p>
</div>
</div>
</div>
<h3 class="section">Public Methods</h3>
<div id="CumulativeDistribution" class="method">
<h4><span title="System.double">double</span> <strong>CumulativeDistribution</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the cumulative distribution at location <var>x</var>. </p>
</div>
</div>
</div>
<div id="Density" class="method">
<h4><span title="System.double">double</span> <strong>Density</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="DensityLn" class="method">
<h4><span title="System.double">double</span> <strong>DensityLn</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the log density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the log density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="Equals" class="method">
<h4><span title="System.bool">bool</span> <strong>Equals</strong>(<span title="System.object">object</span> obj)</h4>
<div class="content">
</div>
</div>
<div id="GetHashCode" class="method">
<h4><span title="System.int">int</span> <strong>GetHashCode</strong>()</h4>
<div class="content">
</div>
</div>
<div id="GetMoment" class="method">
<h4><span title="System.double">double</span> <strong>GetMoment</strong>(<span title="System.double">double</span> n)</h4>
<div class="content">Gets the n-th raw moment of the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> n</h6>
<p class="comments">The order (n) of the moment. Range: n ≥ 1. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the n-th moment of the distribution. </p>
</div>
</div>
</div>
<div id="GetType" class="method">
<h4><span title="System.Type">Type</span> <strong>GetType</strong>()</h4>
<div class="content">
</div>
</div>
<div id="Sample" class="method">
<h4><span title="System.double">double</span> <strong>Sample</strong>()</h4>
<div class="content">Generates a sample from the Burr distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>a sample from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> <strong>Samples</strong>()</h4>
<div class="content">Generates a sequence of samples from the Burr distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code></h6>
<p>a sequence of samples from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Double[]">Double[]</span> values)</h4>
<div class="content">Fills an array with samples generated from the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
<p class="comments">The array to fill with the samples. </p>
</div>
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>()</h4>
<div class="content">A string representation of the distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.string">string</span></code></h6>
<p>a string representation of the distribution. </p>
</div>
</div>
</div>
<h3 class="section">Public Properties</h3>
<div id="a" class="method">
<h4><span title="System.double">double</span> <strong>a</strong> get; </h4>
<div class="content">Gets the scale (a) of the distribution. Range: a > 0.
</div>
</div>
<div id="c" class="method">
<h4><span title="System.double">double</span> <strong>c</strong> get; </h4>
<div class="content">Gets the first shape parameter (c) of the distribution. Range: c > 0.
</div>
</div>
<div id="Entropy" class="method">
<h4><span title="System.double">double</span> <strong>Entropy</strong> get; </h4>
<div class="content">Gets the entropy of the Burr distribution (currently not supported).
</div>
</div>
<div id="k" class="method">
<h4><span title="System.double">double</span> <strong>k</strong> get; </h4>
<div class="content">Gets the second shape parameter (k) of the distribution. Range: k > 0.
</div>
</div>
<div id="Maximum" class="method">
<h4><span title="System.double">double</span> <strong>Maximum</strong> get; </h4>
<div class="content">Gets the maximum of the Burr distribution.
</div>
</div>
<div id="Mean" class="method">
<h4><span title="System.double">double</span> <strong>Mean</strong> get; </h4>
<div class="content">Gets the mean of the Burr distribution.
</div>
</div>
<div id="Median" class="method">
<h4><span title="System.double">double</span> <strong>Median</strong> get; </h4>
<div class="content">Gets the median of the Burr distribution.
</div>
</div>
<div id="Minimum" class="method">
<h4><span title="System.double">double</span> <strong>Minimum</strong> get; </h4>
<div class="content">Gets the minimum of the Burr distribution.
</div>
</div>
<div id="Mode" class="method">
<h4><span title="System.double">double</span> <strong>Mode</strong> get; </h4>
<div class="content">Gets the mode of the Burr distribution.
</div>
</div>
<div id="RandomSource" class="method">
<h4><span title="System.Random">Random</span> <strong>RandomSource</strong> get; set;</h4>
<div class="content">Gets the random number generator which is used to draw random samples.
</div>
</div>
<div id="Skewness" class="method">
<h4><span title="System.double">double</span> <strong>Skewness</strong> get; </h4>
<div class="content">Gets the skewness of the Burr distribution.
</div>
</div>
<div id="StdDev" class="method">
<h4><span title="System.double">double</span> <strong>StdDev</strong> get; </h4>
<div class="content">Gets the standard deviation of the Burr distribution.
</div>
</div>
<div id="Variance" class="method">
<h4><span title="System.double">double</span> <strong>Variance</strong> get; </h4>
<div class="content">Gets the variance of the Burr distribution.
</div>
</div>
<div id="footer">
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@ -192,6 +195,9 @@
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</li>
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<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
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<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -1041,7 +1050,7 @@ at the given probability.
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@ -192,6 +195,9 @@
</li>
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</li>
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@ -240,6 +246,9 @@
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -863,7 +872,7 @@ at the given probability. This is also known as the quantile or percent point fu
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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@ -776,7 +785,7 @@ then have a chi distribution..
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -820,7 +829,7 @@ at the given probability. This is also known as the quantile or percent point fu
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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@ -863,7 +872,7 @@ at the given probability. This is also known as the quantile or percent point fu
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -775,7 +784,7 @@ distributions. It is parameterized by two real numbers "lambda" and "nu". For <d
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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</li>
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -554,7 +563,7 @@ You can also leave out the last <var>x</var> component, and it will be compute
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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@ -806,7 +815,7 @@ is parameterized by a lower and upper bound (both inclusive)..
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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@ -855,7 +864,7 @@ be initialized with the default random number generator.
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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@ -820,7 +829,7 @@ at the given probability. This is also known as the quantile or percent point fu
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@ -240,6 +246,9 @@
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@ -857,7 +866,7 @@ at the given probability. This is also known as the quantile or percent point fu
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@ -240,6 +246,9 @@
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@ -910,7 +919,7 @@ at the given probability. This is also known as the quantile or percent point fu
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@ -240,6 +246,9 @@
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@ -747,7 +756,7 @@ This implementation of the Geometric distribution will never generate 0's..
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<div class="header">
<p class="class"><strong>Type</strong> InverseGaussian</p>
<p><strong>Namespace</strong> MathNet.Numerics.Distributions</p>
<p><strong>Interfaces</strong> <a href="../MathNet.Numerics.Distributions/IContinuousDistribution.htm">IContinuousDistribution</a></p>
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<div class="sub-header">
<h3 class="section">Constructors</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#.ctor">InverseGaussian</a></li>
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<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#CDF">CDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Estimate">Estimate</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#ICDF">ICDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#IsValidParameterSet">IsValidParameterSet</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#PDF">PDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#PDFLn">PDFLn</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Sample">Sample</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Samples">Samples</a></li>
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<h3 class="section">Methods</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#CumulativeDistribution">CumulativeDistribution</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Density">Density</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#DensityLn">DensityLn</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Equals">Equals</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#GetHashCode">GetHashCode</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#GetType">GetType</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#InvCDF">InvCDF</a></li>
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<h3 class="section">Properties</h3>
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<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Entropy">Entropy</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Kurtosis">Kurtosis</a></li>
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<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Maximum">Maximum</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Mean">Mean</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Median">Median</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Minimum">Minimum</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Mode">Mode</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Mu">Mu</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#RandomSource">RandomSource</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Skewness">Skewness</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#StdDev">StdDev</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm#Variance">Variance</a></li>
</ul>
</div>
<h3 class="section">Public Constructors</h3>
<div id=".ctor" class="method">
<h4> <strong>InverseGaussian</strong>(<span title="System.double">double</span> mu, <span title="System.double">double</span> lambda, <span title="System.Random">Random</span> randomSource)</h4>
<div class="content">Initializes a new instance of the InverseGaussian class.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
<p class="comments">The random number generator which is used to draw random samples. </p>
</div>
</div>
</div>
<h3 class="section">Public Static Functions</h3>
<div id="CDF" class="method">
<h4><span title="System.double">double</span> <strong>CDF</strong>(<span title="System.double">double</span> mu, <span title="System.double">double</span> lambda, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the cumulative distribution at location <var>x</var>. </p>
</div>
</div>
</div>
<div id="Estimate" class="method">
<h4><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a> <strong>Estimate</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> samples, <span title="System.Random">Random</span> randomSource)</h4>
<div class="content">Estimates the Inverse Gaussian parameters from sample data with maximum-likelihood.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code> samples</h6>
<p class="comments">The samples to estimate the distribution parameters from. </p>
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
<p class="comments">The random number generator which is used to draw random samples. Optional, can be null. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a></code></h6>
<p>An Inverse Gaussian distribution. </p>
</div>
</div>
</div>
<div id="ICDF" class="method">
<h4><span title="System.double">double</span> <strong>ICDF</strong>(<span title="System.double">double</span> mu, <span title="System.double">double</span> lambda, <span title="System.double">double</span> p)</h4>
<div class="content">Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
<h6><code><span title="System.double">double</span></code> p</h6>
<p class="comments">The location at which to compute the inverse cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the inverse cumulative distribution at location <var>p</var>. </p>
</div>
</div>
</div>
<div id="IsValidParameterSet" class="method">
<h4><span title="System.bool">bool</span> <strong>IsValidParameterSet</strong>(<span title="System.double">double</span> mu, <span title="System.double">double</span> lambda)</h4>
<div class="content">Tests whether the provided values are valid parameters for this distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
</div>
</div>
</div>
<div id="PDF" class="method">
<h4><span title="System.double">double</span> <strong>PDF</strong>(<span title="System.double">double</span> mu, <span title="System.double">double</span> lambda, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="PDFLn" class="method">
<h4><span title="System.double">double</span> <strong>PDFLn</strong>(<span title="System.double">double</span> mu, <span title="System.double">double</span> lambda, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the log density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the log density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="Sample" class="method">
<h4><span title="System.double">double</span> <strong>Sample</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> mu, <span title="System.double">double</span> lambda)</h4>
<div class="content">Generates a sample from the inverse Gaussian distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>a sample from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.Double[]">Double[]</span> values, <span title="System.double">double</span> mu, <span title="System.double">double</span> lambda)</h4>
<div class="content">Fills an array with samples generated from the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
<p class="comments">The array to fill with the samples. </p>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> mu, <span title="System.double">double</span> lambda)</h4>
<div class="content">Generates a sequence of samples from the Burr distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.double">double</span></code> mu</h6>
<p class="comments">The mean (μ) of the distribution. Range: μ > 0. </p>
<h6><code><span title="System.double">double</span></code> lambda</h6>
<p class="comments">The shape (λ) of the distribution. Range: λ > 0. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code></h6>
<p>a sequence of samples from the distribution. </p>
</div>
</div>
</div>
<h3 class="section">Public Methods</h3>
<div id="CumulativeDistribution" class="method">
<h4><span title="System.double">double</span> <strong>CumulativeDistribution</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the cumulative distribution at location <var>x</var>. </p>
</div>
</div>
</div>
<div id="Density" class="method">
<h4><span title="System.double">double</span> <strong>Density</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="DensityLn" class="method">
<h4><span title="System.double">double</span> <strong>DensityLn</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the log density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the log density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="Equals" class="method">
<h4><span title="System.bool">bool</span> <strong>Equals</strong>(<span title="System.object">object</span> obj)</h4>
<div class="content">
</div>
</div>
<div id="GetHashCode" class="method">
<h4><span title="System.int">int</span> <strong>GetHashCode</strong>()</h4>
<div class="content">
</div>
</div>
<div id="GetType" class="method">
<h4><span title="System.Type">Type</span> <strong>GetType</strong>()</h4>
<div class="content">
</div>
</div>
<div id="InvCDF" class="method">
<h4><span title="System.double">double</span> <strong>InvCDF</strong>(<span title="System.double">double</span> p)</h4>
<div class="content">Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> p</h6>
<p class="comments">The location at which to compute the inverse cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the inverse cumulative distribution at location <var>p</var>. </p>
</div>
</div>
</div>
<div id="Sample" class="method">
<h4><span title="System.double">double</span> <strong>Sample</strong>()</h4>
<div class="content">Generates a sample from the inverse Gaussian distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>a sample from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Double[]">Double[]</span> values)</h4>
<div class="content">Fills an array with samples generated from the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
<p class="comments">The array to fill with the samples. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> <strong>Samples</strong>()</h4>
<div class="content">Generates a sequence of samples from the inverse Gaussian distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code></h6>
<p>a sequence of samples from the distribution. </p>
</div>
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>()</h4>
<div class="content">A string representation of the distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.string">string</span></code></h6>
<p>a string representation of the distribution. </p>
</div>
</div>
</div>
<h3 class="section">Public Properties</h3>
<div id="Entropy" class="method">
<h4><span title="System.double">double</span> <strong>Entropy</strong> get; </h4>
<div class="content">Gets the entropy of the Inverse Gaussian distribution (currently not supported).
</div>
</div>
<div id="Kurtosis" class="method">
<h4><span title="System.double">double</span> <strong>Kurtosis</strong> get; </h4>
<div class="content">Gets the kurtosis of the Inverse Gaussian distribution.
</div>
</div>
<div id="Lambda" class="method">
<h4><span title="System.double">double</span> <strong>Lambda</strong> get; </h4>
<div class="content">Gets the shape (λ) of the distribution. Range: λ > 0.
</div>
</div>
<div id="Maximum" class="method">
<h4><span title="System.double">double</span> <strong>Maximum</strong> get; </h4>
<div class="content">Gets the maximum of the Inverse Gaussian distribution.
</div>
</div>
<div id="Mean" class="method">
<h4><span title="System.double">double</span> <strong>Mean</strong> get; </h4>
<div class="content">Gets the mean of the Inverse Gaussian distribution.
</div>
</div>
<div id="Median" class="method">
<h4><span title="System.double">double</span> <strong>Median</strong> get; </h4>
<div class="content">Gets the median of the Inverse Gaussian distribution.
No closed form analytical expression exists, so this value is approximated numerically and can throw an exception.
</div>
</div>
<div id="Minimum" class="method">
<h4><span title="System.double">double</span> <strong>Minimum</strong> get; </h4>
<div class="content">Gets the minimum of the Inverse Gaussian distribution.
</div>
</div>
<div id="Mode" class="method">
<h4><span title="System.double">double</span> <strong>Mode</strong> get; </h4>
<div class="content">Gets the mode of the Inverse Gaussian distribution.
</div>
</div>
<div id="Mu" class="method">
<h4><span title="System.double">double</span> <strong>Mu</strong> get; </h4>
<div class="content">Gets the mean (μ) of the distribution. Range: μ > 0.
</div>
</div>
<div id="RandomSource" class="method">
<h4><span title="System.Random">Random</span> <strong>RandomSource</strong> get; set;</h4>
<div class="content">Gets the random number generator which is used to draw random samples.
</div>
</div>
<div id="Skewness" class="method">
<h4><span title="System.double">double</span> <strong>Skewness</strong> get; </h4>
<div class="content">Gets the skewness of the Inverse Gaussian distribution.
</div>
</div>
<div id="StdDev" class="method">
<h4><span title="System.double">double</span> <strong>StdDev</strong> get; </h4>
<div class="content">Gets the standard deviation of the Inverse Gaussian distribution.
</div>
</div>
<div id="Variance" class="method">
<h4><span title="System.double">double</span> <strong>Variance</strong> get; </h4>
<div class="content">Gets the variance of the Inverse Gaussian distribution.
</div>
</div>
<div id="footer">
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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</li>
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<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
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<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
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<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
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<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
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<a href="../MathNet.Numerics.Distributions/InverseWishart.htm" class="current">InverseWishart</a>
@ -240,6 +246,9 @@
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<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -511,7 +520,7 @@ a Wishart random variable and inverting the matrix.
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@ -192,6 +195,9 @@
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@ -240,6 +246,9 @@
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -817,7 +826,7 @@ p(x) = \frac{1}{2 * scale} \exp{- |x - mean| / scale}..
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@ -936,7 +945,7 @@ at the given probability. This is also known as the quantile or percent point fu
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</div><div id="types">
<h2 class="fixed">Types in MathNet.Numerics.Distributions</h2>
<div class="scroll">
<ul>
<li>
<a href="../MathNet.Numerics.Distributions/Bernoulli.htm">Bernoulli</a>
</li>
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<a href="../MathNet.Numerics.Distributions/Beta.htm">Beta</a>
</li>
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<a href="../MathNet.Numerics.Distributions/BetaScaled.htm">BetaScaled</a>
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<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
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<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
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<a href="../MathNet.Numerics.Distributions/Cauchy.htm">Cauchy</a>
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<a href="../MathNet.Numerics.Distributions/Chi.htm">Chi</a>
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<a href="../MathNet.Numerics.Distributions/ContinuousUniform.htm">ContinuousUniform</a>
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<a href="../MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm">ConwayMaxwellPoisson</a>
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<a href="../MathNet.Numerics.Distributions/Dirichlet.htm">Dirichlet</a>
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<a href="../MathNet.Numerics.Distributions/IDistribution.htm">IDistribution</a>
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<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
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<a href="../MathNet.Numerics.Distributions/NormalGamma.htm">NormalGamma</a>
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<a href="../MathNet.Numerics.Distributions/Pareto.htm">Pareto</a>
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<a href="../MathNet.Numerics.Distributions/Poisson.htm">Poisson</a>
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<a href="../MathNet.Numerics.Distributions/Rayleigh.htm">Rayleigh</a>
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<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
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<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm" class="current">TruncatedPareto</a>
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<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
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<a href="../MathNet.Numerics.Distributions/Wishart.htm">Wishart</a>
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<a href="../MathNet.Numerics.Distributions/Zipf.htm">Zipf</a>
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</ul>
</div>
</div>
<div class="header">
<p class="class"><strong>Type</strong> TruncatedPareto</p>
<p><strong>Namespace</strong> MathNet.Numerics.Distributions</p>
<p><strong>Interfaces</strong> <a href="../MathNet.Numerics.Distributions/IContinuousDistribution.htm">IContinuousDistribution</a></p>
</div>
<div class="sub-header">
<h3 class="section">Constructors</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#.ctor">TruncatedPareto</a></li>
</ul>
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#CDF">CDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#ICDF">ICDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#IsValidParameterSet">IsValidParameterSet</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#PDF">PDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#PDFLn">PDFLn</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Sample">Sample</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Samples">Samples</a></li>
</ul>
<h3 class="section">Methods</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#CumulativeDistribution">CumulativeDistribution</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Density">Density</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#DensityLn">DensityLn</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Equals">Equals</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#GetHashCode">GetHashCode</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#GetMoment">GetMoment</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#GetType">GetType</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#InvCDF">InvCDF</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Sample">Sample</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Samples">Samples</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#ToString">ToString</a></li>
</ul>
<h3 class="section">Properties</h3>
<ul>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Entropy">Entropy</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Maximum">Maximum</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Mean">Mean</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Median">Median</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Minimum">Minimum</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Mode">Mode</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#RandomSource">RandomSource</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Scale">Scale</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Shape">Shape</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Skewness">Skewness</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#StdDev">StdDev</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Truncation">Truncation</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm#Variance">Variance</a></li>
</ul>
</div>
<h3 class="section">Public Constructors</h3>
<div id=".ctor" class="method">
<h4> <strong>TruncatedPareto</strong>(<span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation, <span title="System.Random">Random</span> randomSource)</h4>
<div class="content">Initializes a new instance of the TruncatedPareto class.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
<p class="comments">The random number generator which is used to draw random samples. </p>
</div>
</div>
</div>
<h3 class="section">Public Static Functions</h3>
<div id="CDF" class="method">
<h4><span title="System.double">double</span> <strong>CDF</strong>(<span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the cumulative distribution at location <var>x</var>. </p>
</div>
</div>
</div>
<div id="ICDF" class="method">
<h4><span title="System.double">double</span> <strong>ICDF</strong>(<span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation, <span title="System.double">double</span> p)</h4>
<div class="content">Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
<h6><code><span title="System.double">double</span></code> p</h6>
<p class="comments">The location at which to compute the inverse cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the inverse cumulative distribution at location <var>p</var>. </p>
</div>
</div>
</div>
<div id="IsValidParameterSet" class="method">
<h4><span title="System.bool">bool</span> <strong>IsValidParameterSet</strong>(<span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation)</h4>
<div class="content">Tests whether the provided values are valid parameters for this distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
</div>
</div>
</div>
<div id="PDF" class="method">
<h4><span title="System.double">double</span> <strong>PDF</strong>(<span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="PDFLn" class="method">
<h4><span title="System.double">double</span> <strong>PDFLn</strong>(<span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation, <span title="System.double">double</span> x)</h4>
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the log density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the log density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="Sample" class="method">
<h4><span title="System.double">double</span> <strong>Sample</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation)</h4>
<div class="content">Generates a sample from the truncated Pareto distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>a sample from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.Double[]">Double[]</span> values, <span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation)</h4>
<div class="content">Fills an array with samples generated from the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
<p class="comments">The array to fill with the samples. </p>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> scale, <span title="System.double">double</span> shape, <span title="System.double">double</span> truncation)</h4>
<div class="content">Generates a sequence of samples from the truncated Pareto distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
<p class="comments">The random number generator to use. </p>
<h6><code><span title="System.double">double</span></code> scale</h6>
<p class="comments">The scale (xm) of the distribution. Range: xm > 0. </p>
<h6><code><span title="System.double">double</span></code> shape</h6>
<p class="comments">The shape (α) of the distribution. Range: α > 0. </p>
<h6><code><span title="System.double">double</span></code> truncation</h6>
<p class="comments">The truncation (T) of the distribution. Range: T > xm. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code></h6>
<p>a sequence of samples from the distribution. </p>
</div>
</div>
</div>
<h3 class="section">Public Methods</h3>
<div id="CumulativeDistribution" class="method">
<h4><span title="System.double">double</span> <strong>CumulativeDistribution</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the cumulative distribution at location <var>x</var>. </p>
</div>
</div>
</div>
<div id="Density" class="method">
<h4><span title="System.double">double</span> <strong>Density</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="DensityLn" class="method">
<h4><span title="System.double">double</span> <strong>DensityLn</strong>(<span title="System.double">double</span> x)</h4>
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> x</h6>
<p class="comments">The location at which to compute the log density. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the log density at <var>x</var>. </p>
</div>
</div>
</div>
<div id="Equals" class="method">
<h4><span title="System.bool">bool</span> <strong>Equals</strong>(<span title="System.object">object</span> obj)</h4>
<div class="content">
</div>
</div>
<div id="GetHashCode" class="method">
<h4><span title="System.int">int</span> <strong>GetHashCode</strong>()</h4>
<div class="content">
</div>
</div>
<div id="GetMoment" class="method">
<h4><span title="System.double">double</span> <strong>GetMoment</strong>(<span title="System.int">int</span> n)</h4>
<div class="content">Gets the n-th raw moment of the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.int">int</span></code> n</h6>
<p class="comments">The order (n) of the moment. Range: n ≥ 1. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the n-th moment of the distribution. </p>
</div>
</div>
</div>
<div id="GetType" class="method">
<h4><span title="System.Type">Type</span> <strong>GetType</strong>()</h4>
<div class="content">
</div>
</div>
<div id="InvCDF" class="method">
<h4><span title="System.double">double</span> <strong>InvCDF</strong>(<span title="System.double">double</span> p)</h4>
<div class="content">Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.double">double</span></code> p</h6>
<p class="comments">The location at which to compute the inverse cumulative distribution function. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>the inverse cumulative distribution at location <var>p</var>. </p>
</div>
</div>
</div>
<div id="Sample" class="method">
<h4><span title="System.double">double</span> <strong>Sample</strong>()</h4>
<div class="content">Generates a sample from the truncated Pareto distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.double">double</span></code></h6>
<p>a sample from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> <strong>Samples</strong>()</h4>
<div class="content">Generates a sequence of samples from the truncated Pareto distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span></code></h6>
<p>a sequence of samples from the distribution. </p>
</div>
</div>
</div>
<div id="Samples" class="method">
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Double[]">Double[]</span> values)</h4>
<div class="content">Fills an array with samples generated from the distribution.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
<p class="comments">The array to fill with the samples. </p>
</div>
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>()</h4>
<div class="content">A string representation of the distribution.
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.string">string</span></code></h6>
<p>a string representation of the distribution. </p>
</div>
</div>
</div>
<h3 class="section">Public Properties</h3>
<div id="Entropy" class="method">
<h4><span title="System.double">double</span> <strong>Entropy</strong> get; </h4>
<div class="content">Gets the entropy of the truncated Pareto distribution (not supported).
</div>
</div>
<div id="Maximum" class="method">
<h4><span title="System.double">double</span> <strong>Maximum</strong> get; </h4>
<div class="content">Gets the maximum of the truncated Pareto distribution.
</div>
</div>
<div id="Mean" class="method">
<h4><span title="System.double">double</span> <strong>Mean</strong> get; </h4>
<div class="content">Gets the mean of the truncated Pareto distribution.
</div>
</div>
<div id="Median" class="method">
<h4><span title="System.double">double</span> <strong>Median</strong> get; </h4>
<div class="content">Gets the median of the truncated Pareto distribution.
</div>
</div>
<div id="Minimum" class="method">
<h4><span title="System.double">double</span> <strong>Minimum</strong> get; </h4>
<div class="content">Gets the minimum of the truncated Pareto distribution.
</div>
</div>
<div id="Mode" class="method">
<h4><span title="System.double">double</span> <strong>Mode</strong> get; </h4>
<div class="content">Gets the mode of the truncated Pareto distribution (not supported).
</div>
</div>
<div id="RandomSource" class="method">
<h4><span title="System.Random">Random</span> <strong>RandomSource</strong> get; set;</h4>
<div class="content">Gets the random number generator which is used to draw random samples.
</div>
</div>
<div id="Scale" class="method">
<h4><span title="System.double">double</span> <strong>Scale</strong> get; </h4>
<div class="content">Gets the scale (xm) of the distribution. Range: xm > 0.
</div>
</div>
<div id="Shape" class="method">
<h4><span title="System.double">double</span> <strong>Shape</strong> get; </h4>
<div class="content">Gets the shape (α) of the distribution. Range: α > 0.
</div>
</div>
<div id="Skewness" class="method">
<h4><span title="System.double">double</span> <strong>Skewness</strong> get; </h4>
<div class="content">Gets the skewness of the truncated Pareto distribution.
</div>
</div>
<div id="StdDev" class="method">
<h4><span title="System.double">double</span> <strong>StdDev</strong> get; </h4>
<div class="content">Gets the standard deviation of the truncated Pareto distribution.
</div>
</div>
<div id="Truncation" class="method">
<h4><span title="System.double">double</span> <strong>Truncation</strong> get; </h4>
<div class="content">Gets the truncation (T) of the distribution. Range: T > 0.
</div>
</div>
<div id="Variance" class="method">
<h4><span title="System.double">double</span> <strong>Variance</strong> get; </h4>
<div class="content">Gets the variance of the truncated Pareto distribution.
</div>
</div>
<div id="footer">
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>
</html>

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@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm" class="current">Weibull</a>
@ -822,7 +831,7 @@ For details about this distribution, see. <blockquote class="remarks">
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

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@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -512,7 +521,7 @@ Applied Statistics, Vol. 21, No. 3 (1972), pp. 341-345
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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</div>
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@ -138,6 +138,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -192,6 +195,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -240,6 +246,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -778,7 +787,7 @@ For details about this distribution, see.
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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</div>
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@ -137,6 +137,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a>
@ -191,6 +194,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a>
@ -239,6 +245,9 @@
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
</li>
<li>
<a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a>
@ -262,6 +271,7 @@
<li><a href="../MathNet.Numerics.Distributions/Beta.htm">Beta</a></li>
<li><a href="../MathNet.Numerics.Distributions/BetaScaled.htm">BetaScaled</a></li>
<li><a href="../MathNet.Numerics.Distributions/Binomial.htm">Binomial</a></li>
<li><a href="../MathNet.Numerics.Distributions/Burr.htm">Burr</a></li>
<li><a href="../MathNet.Numerics.Distributions/Categorical.htm">Categorical</a></li>
<li><a href="../MathNet.Numerics.Distributions/Cauchy.htm">Cauchy</a></li>
<li><a href="../MathNet.Numerics.Distributions/Chi.htm">Chi</a></li>
@ -277,6 +287,7 @@
<li><a href="../MathNet.Numerics.Distributions/Geometric.htm">Geometric</a></li>
<li><a href="../MathNet.Numerics.Distributions/Hypergeometric.htm">Hypergeometric</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGamma.htm">InverseGamma</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseGaussian.htm">InverseGaussian</a></li>
<li><a href="../MathNet.Numerics.Distributions/InverseWishart.htm">InverseWishart</a></li>
<li><a href="../MathNet.Numerics.Distributions/Laplace.htm">Laplace</a></li>
<li><a href="../MathNet.Numerics.Distributions/LogNormal.htm">LogNormal</a></li>
@ -292,6 +303,7 @@
<li><a href="../MathNet.Numerics.Distributions/Stable.htm">Stable</a></li>
<li><a href="../MathNet.Numerics.Distributions/StudentT.htm">StudentT</a></li>
<li><a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a></li>
<li><a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a></li>
<li><a href="../MathNet.Numerics.Distributions/Weibull.htm">Weibull</a></li>
<li><a href="../MathNet.Numerics.Distributions/Wishart.htm">Wishart</a></li>
<li><a href="../MathNet.Numerics.Distributions/Zipf.htm">Zipf</a></li>
@ -306,7 +318,7 @@
</ul>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
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@ -196,7 +196,7 @@ and then dividing the total by the number of loss periods. <blockquote class="re
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<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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@ -219,7 +219,7 @@ looks at periods where the investment return was less than average return.
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<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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@ -147,7 +147,7 @@
</div>
<div id="footer">
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<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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@ -203,7 +203,7 @@
<h3 class="section">Public Static Functions</h3>
<div id="BluesteinForward" class="method">
<h4><span title="System.void">void</span> <strong>BluesteinForward</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>BluesteinForward</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Bluestein forward FFT for arbitrary sized sample vectors.
<div id="warning">
<b>Obsolete:</b> Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then.
@ -213,7 +213,7 @@
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -223,7 +223,7 @@
</div>
</div>
<div id="BluesteinForward" class="method">
<h4><span title="System.void">void</span> <strong>BluesteinForward</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>BluesteinForward</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Bluestein forward FFT for arbitrary sized sample vectors.
<div id="warning">
<b>Obsolete:</b> Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then.
@ -233,7 +233,7 @@
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -313,15 +313,17 @@
</div>
</div>
<div id="Forward" class="method">
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="System.Single[]">Single[]</span> real, <span title="System.Single[]">Single[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Single[]">Single[]</span></code> real</h6>
<p class="comments">Real part of the sample vector, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Single[]">Single[]</span></code> imaginary</h6>
<p class="comments">Imaginary part of the sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
</div>
@ -330,14 +332,14 @@
</div>
</div>
<div id="Forward" class="method">
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -347,16 +349,16 @@
</div>
</div>
<div id="Forward" class="method">
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="System.Single[]">Single[]</span> real, <span title="System.Single[]">Single[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="System.Double[]">Double[]</span> real, <span title="System.Double[]">Double[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Single[]">Single[]</span></code> real</h6>
<h6><code><span title="System.Double[]">Double[]</span></code> real</h6>
<p class="comments">Real part of the sample vector, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Single[]">Single[]</span></code> imaginary</h6>
<h6><code><span title="System.Double[]">Double[]</span></code> imaginary</h6>
<p class="comments">Imaginary part of the sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -366,17 +368,15 @@
</div>
</div>
<div id="Forward" class="method">
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="System.Double[]">Double[]</span> real, <span title="System.Double[]">Double[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Forward</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> real</h6>
<p class="comments">Real part of the sample vector, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Double[]">Double[]</span></code> imaginary</h6>
<p class="comments">Imaginary part of the sample vector, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
</div>
@ -448,14 +448,14 @@
</div>
</div>
<div id="ForwardMultiDim" class="method">
<h4><span title="System.void">void</span> <strong>ForwardMultiDim</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <span title="System.Int32[]">Int32[]</span> dimensions, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>ForwardMultiDim</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <span title="System.Int32[]">Int32[]</span> dimensions, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the forward Fast Fourier Transform (FFT) to multiple dimensional sample data.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<p class="comments">Sample data, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Int32[]">Int32[]</span></code> dimensions</h6>
<p class="comments">The data size per dimension. The first dimension is the major one.
@ -468,14 +468,14 @@ For example, with two dimensions "rows" and "columns" the samples are assumed to
</div>
</div>
<div id="ForwardMultiDim" class="method">
<h4><span title="System.void">void</span> <strong>ForwardMultiDim</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <span title="System.Int32[]">Int32[]</span> dimensions, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>ForwardMultiDim</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <span title="System.Int32[]">Int32[]</span> dimensions, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the forward Fast Fourier Transform (FFT) to multiple dimensional sample data.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<p class="comments">Sample data, where the FFT is evaluated in place. </p>
<h6><code><span title="System.Int32[]">Int32[]</span></code> dimensions</h6>
<p class="comments">The data size per dimension. The first dimension is the major one.
@ -488,17 +488,17 @@ For example, with two dimensions "rows" and "columns" the samples are assumed to
</div>
</div>
<div id="ForwardReal" class="method">
<h4><span title="System.void">void</span> <strong>ForwardReal</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>ForwardReal</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Packed Real-Complex forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
Since for real-valued time samples the complex spectrum is conjugate-even (symmetry),
the spectrum can be fully reconstructed form the positive frequencies only (first half).
the spectrum can be fully reconstructed from the positive frequencies only (first half).
The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order to support such a packed spectrum.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
<p class="comments">Data array of length N+2 (if N is even) or N+1 (if N is odd). </p>
<h6><code><span title="System.int">int</span></code> n</h6>
<p class="comments">The number of samples. </p>
@ -510,17 +510,17 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
</div>
</div>
<div id="ForwardReal" class="method">
<h4><span title="System.void">void</span> <strong>ForwardReal</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>ForwardReal</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Packed Real-Complex forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
Since for real-valued time samples the complex spectrum is conjugate-even (symmetry),
the spectrum can be fully reconstructed from the positive frequencies only (first half).
the spectrum can be fully reconstructed form the positive frequencies only (first half).
The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order to support such a packed spectrum.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
<p class="comments">Data array of length N+2 (if N is even) or N+1 (if N is odd). </p>
<h6><code><span title="System.int">int</span></code> n</h6>
<p class="comments">The number of samples. </p>
@ -553,22 +553,26 @@ followed by the negative frequencies wrapped around.
</div>
</div>
<div id="Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> spectrum)</h4>
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Single[]">Single[]</span> real, <span title="System.Single[]">Single[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> spectrum</h6>
<p class="comments">Spectrum data, where the iFFT is evaluated in place. </p>
<h6><code><span title="System.Single[]">Single[]</span></code> real</h6>
<p class="comments">Real part of the sample vector, where the iFFT is evaluated in place. </p>
<h6><code><span title="System.Single[]">Single[]</span></code> imaginary</h6>
<p class="comments">Imaginary part of the sample vector, where the iFFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
</div>
</div>
</div>
<div id="Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> spectrum)</h4>
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> spectrum, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
@ -577,6 +581,8 @@ followed by the negative frequencies wrapped around.
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> spectrum</h6>
<p class="comments">Spectrum data, where the iFFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
</div>
@ -600,33 +606,31 @@ followed by the negative frequencies wrapped around.
</div>
</div>
<div id="Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> spectrum, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> spectrum)</h4>
<div class="content">Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> spectrum</h6>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> spectrum</h6>
<p class="comments">Spectrum data, where the iFFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
</div>
</div>
</div>
<div id="Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Single[]">Single[]</span> real, <span title="System.Single[]">Single[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Double[]">Double[]</span> real, <span title="System.Double[]">Double[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Single[]">Single[]</span></code> real</h6>
<h6><code><span title="System.Double[]">Double[]</span></code> real</h6>
<p class="comments">Real part of the sample vector, where the iFFT is evaluated in place. </p>
<h6><code><span title="System.Single[]">Single[]</span></code> imaginary</h6>
<h6><code><span title="System.Double[]">Double[]</span></code> imaginary</h6>
<p class="comments">Imaginary part of the sample vector, where the iFFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -636,19 +640,15 @@ followed by the negative frequencies wrapped around.
</div>
</div>
<div id="Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Double[]">Double[]</span> real, <span title="System.Double[]">Double[]</span> imaginary, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Inverse</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> spectrum)</h4>
<div class="content">Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> real</h6>
<p class="comments">Real part of the sample vector, where the iFFT is evaluated in place. </p>
<h6><code><span title="System.Double[]">Double[]</span></code> imaginary</h6>
<p class="comments">Imaginary part of the sample vector, where the iFFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> spectrum</h6>
<p class="comments">Spectrum data, where the iFFT is evaluated in place. </p>
</div>
@ -758,7 +758,7 @@ For example, with two dimensions "rows" and "columns" the samples are assumed to
</div>
</div>
<div id="InverseReal" class="method">
<h4><span title="System.void">void</span> <strong>InverseReal</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>InverseReal</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Packed Real-Complex inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
Since for real-valued time samples the complex spectrum is conjugate-even (symmetry),
the spectrum can be fully reconstructed form the positive frequencies only (first half).
@ -768,7 +768,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
<p class="comments">Data array of length N+2 (if N is even) or N+1 (if N is odd). </p>
<h6><code><span title="System.int">int</span></code> n</h6>
<p class="comments">The number of samples. </p>
@ -780,7 +780,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
</div>
</div>
<div id="InverseReal" class="method">
<h4><span title="System.void">void</span> <strong>InverseReal</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>InverseReal</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.int">int</span> n, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Packed Real-Complex inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
Since for real-valued time samples the complex spectrum is conjugate-even (symmetry),
the spectrum can be fully reconstructed form the positive frequencies only (first half).
@ -790,7 +790,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
<p class="comments">Data array of length N+2 (if N is even) or N+1 (if N is odd). </p>
<h6><code><span title="System.int">int</span></code> n</h6>
<p class="comments">The number of samples. </p>
@ -902,7 +902,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
</div>
</div>
<div id="Radix2Forward" class="method">
<h4><span title="System.void">void</span> <strong>Radix2Forward</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Radix2Forward</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Radix-2 forward FFT for power-of-two sized sample vectors.
<div id="warning">
<b>Obsolete:</b> Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then.
@ -912,7 +912,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -922,7 +922,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
</div>
</div>
<div id="Radix2Forward" class="method">
<h4><span title="System.void">void</span> <strong>Radix2Forward</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Radix2Forward</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> samples, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Radix-2 forward FFT for power-of-two sized sample vectors.
<div id="warning">
<b>Obsolete:</b> Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then.
@ -932,7 +932,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> samples</h6>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> samples</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -942,7 +942,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
</div>
</div>
<div id="Radix2Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Radix2Inverse</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> spectrum, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Radix2Inverse</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> spectrum, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Radix-2 inverse FFT for power-of-two sized sample vectors.
<div id="warning">
<b>Obsolete:</b> Use Inverse instead. Will be dropped in version 5.0 and behave like Inverse until then.
@ -952,7 +952,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> spectrum</h6>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> spectrum</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -962,7 +962,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
</div>
</div>
<div id="Radix2Inverse" class="method">
<h4><span title="System.void">void</span> <strong>Radix2Inverse</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> spectrum, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<h4><span title="System.void">void</span> <strong>Radix2Inverse</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> spectrum, <a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a> options)</h4>
<div class="content">Radix-2 inverse FFT for power-of-two sized sample vectors.
<div id="warning">
<b>Obsolete:</b> Use Inverse instead. Will be dropped in version 5.0 and behave like Inverse until then.
@ -972,7 +972,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> spectrum</h6>
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> spectrum</h6>
<p class="comments">Sample vector, where the FFT is evaluated in place. </p>
<h6><code><a href="../MathNet.Numerics.IntegralTransforms/FourierOptions.htm">FourierOptions</a></code> options</h6>
<p class="comments">Fourier Transform Convention Options. </p>
@ -984,7 +984,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

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@ -261,8 +261,11 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -270,11 +273,8 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -369,7 +369,7 @@
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
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@ -212,7 +212,7 @@
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

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@ -258,8 +258,11 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -267,11 +270,8 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -330,7 +330,7 @@
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

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@ -155,7 +155,7 @@
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
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@ -129,6 +129,9 @@
<ul>
<li>
<a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm" class="current">DoubleExponentialTransformation</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm">GaussKronrodRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm">GaussLegendreRule</a>
@ -154,6 +157,7 @@ or derivative discontinuities and no poles inside the interval.
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm#ContourIntegrate">ContourIntegrate</a></li>
<li><a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm#Integrate">Integrate</a></li>
</ul>
@ -165,6 +169,32 @@ or derivative discontinuities and no poles inside the interval.
<h3 class="section">Public Static Functions</h3>
<div id="ContourIntegrate" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrate</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.double">double</span> targetRelativeError)</h4>
<div class="content">Approximate the integral by the double exponential transformation
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span></code> f</h6>
<p class="comments">The analytic smooth complex function to integrate, defined on the real domain. </p>
<h6><code><span title="System.double">double</span></code> intervalBegin</h6>
<p class="comments">Where the interval starts, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> intervalEnd</h6>
<p class="comments">Where the interval stops, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> targetRelativeError</h6>
<p class="comments">The expected relative accuracy of the approximation. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Numerics.Complex">Complex</span></code></h6>
<p>Approximation of the finite integral in the given interval. </p>
</div>
</div>
</div>
<div id="Integrate" class="method">
<h4><span title="System.double">double</span> <strong>Integrate</strong>(<span title="System.Func<double, double>">Func&lt;double, double&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.double">double</span> targetRelativeError)</h4>
<div class="content">Approximate the integral by the double exponential transformation
@ -194,7 +224,7 @@ or derivative discontinuities and no poles inside the interval.
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

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</div>
</div><div id="types">
<h2 class="fixed">Types in MathNet.Numerics.Integration</h2>
<div class="scroll">
<ul>
<li>
<a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm">DoubleExponentialTransformation</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm" class="current">GaussKronrodRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm">GaussLegendreRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm">NewtonCotesTrapeziumRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/SimpsonRule.htm">SimpsonRule</a>
</li>
</ul>
</div>
</div>
<div class="header">
<p class="class"><strong>Type</strong> GaussKronrodRule</p>
<p><strong>Namespace</strong> MathNet.Numerics.Integration</p>
</div>
<div class="sub-header">
<h3 class="section">Constructors</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#.ctor">GaussKronrodRule</a></li>
</ul>
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#ContourIntegrate">ContourIntegrate</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#Integrate">Integrate</a></li>
</ul>
<h3 class="section">Methods</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#Equals">Equals</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#GetHashCode">GetHashCode</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#GetType">GetType</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#ToString">ToString</a></li>
</ul>
<h3 class="section">Properties</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#GaussWeights">GaussWeights</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#KronrodAbscissas">KronrodAbscissas</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#KronrodWeights">KronrodWeights</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm#Order">Order</a></li>
</ul>
</div>
<h3 class="section">Public Constructors</h3>
<div id=".ctor" class="method">
<h4> <strong>GaussKronrodRule</strong>(<span title="System.int">int</span> order)</h4>
<div class="content">
</div>
</div>
<h3 class="section">Public Static Functions</h3>
<div id="ContourIntegrate" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrate</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.Double&">Double&amp;</span> error, <span title="System.Double&">Double&amp;</span> L1Norm, <span title="System.double">double</span> targetRelativeError, <span title="System.int">int</span> maximumDepth, <span title="System.int">int</span> order)</h4>
<div class="content">
</div>
</div>
<div id="Integrate" class="method">
<h4><span title="System.double">double</span> <strong>Integrate</strong>(<span title="System.Func<double, double>">Func&lt;double, double&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.Double&">Double&amp;</span> error, <span title="System.Double&">Double&amp;</span> L1Norm, <span title="System.double">double</span> targetRelativeError, <span title="System.int">int</span> maximumDepth, <span title="System.int">int</span> order)</h4>
<div class="content">
</div>
</div>
<h3 class="section">Public Methods</h3>
<div id="Equals" class="method">
<h4><span title="System.bool">bool</span> <strong>Equals</strong>(<span title="System.object">object</span> obj)</h4>
<div class="content">
</div>
</div>
<div id="GetHashCode" class="method">
<h4><span title="System.int">int</span> <strong>GetHashCode</strong>()</h4>
<div class="content">
</div>
</div>
<div id="GetType" class="method">
<h4><span title="System.Type">Type</span> <strong>GetType</strong>()</h4>
<div class="content">
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>()</h4>
<div class="content">
</div>
</div>
<h3 class="section">Public Properties</h3>
<div id="GaussWeights" class="method">
<h4><span title="System.Double[]">Double[]</span> <strong>GaussWeights</strong> get; </h4>
<div class="content">Getter that returns a clone of the array containing the Gauss weights.
</div>
</div>
<div id="KronrodAbscissas" class="method">
<h4><span title="System.Double[]">Double[]</span> <strong>KronrodAbscissas</strong> get; </h4>
<div class="content">Getter that returns a clone of the array containing the Kronrod abscissas.
</div>
</div>
<div id="KronrodWeights" class="method">
<h4><span title="System.Double[]">Double[]</span> <strong>KronrodWeights</strong> get; </h4>
<div class="content">Getter that returns a clone of the array containing the Kronrod weights.
</div>
</div>
<div id="Order" class="method">
<h4><span title="System.int">int</span> <strong>Order</strong> get; </h4>
<div class="content">Getter for the order.
</div>
</div>
<div id="footer">
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
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</html>

32
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@ -129,6 +129,9 @@
<ul>
<li>
<a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm">DoubleExponentialTransformation</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm">GaussKronrodRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm" class="current">GaussLegendreRule</a>
@ -157,6 +160,7 @@
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm#ContourIntegrate">ContourIntegrate</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm#Integrate">Integrate</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm#Integrate">Integrate</a></li>
</ul>
@ -207,6 +211,32 @@
<h3 class="section">Public Static Functions</h3>
<div id="ContourIntegrate" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrate</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> invervalBegin, <span title="System.double">double</span> invervalEnd, <span title="System.int">int</span> order)</h4>
<div class="content">Approximates a definite integral using an Nth order Gauss-Legendre rule.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span></code> f</h6>
<p class="comments">The analytic smooth complex function to integrate, defined on the real domain. </p>
<h6><code><span title="System.double">double</span></code> invervalBegin</h6>
<p class="comments">Where the interval starts, exclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> invervalEnd</h6>
<p class="comments">Where the interval ends, exclusive and finite. </p>
<h6><code><span title="System.int">int</span></code> order</h6>
<p class="comments">Defines an Nth order Gauss-Legendre rule. The order also defines the number of abscissas and weights for the rule. Precomputed Gauss-Legendre abscissas/weights for orders 2-20, 32, 64, 96, 100, 128, 256, 512, 1024 are used, otherwise they're calculated on the fly. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Numerics.Complex">Complex</span></code></h6>
<p>Approximation of the finite integral in the given interval. </p>
</div>
</div>
</div>
<div id="Integrate" class="method">
<h4><span title="System.double">double</span> <strong>Integrate</strong>(<span title="System.Func<double, double>">Func&lt;double, double&gt;</span> f, <span title="System.double">double</span> invervalBegin, <span title="System.double">double</span> invervalEnd, <span title="System.int">int</span> order)</h4>
<div class="content">Approximates a definite integral using an Nth order Gauss-Legendre rule.
@ -376,7 +406,7 @@
</div>
</div>
<div id="footer">
<p>Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
</div>
</body>

117
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@ -129,6 +129,9 @@
<ul>
<li>
<a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm">DoubleExponentialTransformation</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm">GaussKronrodRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm">GaussLegendreRule</a>
@ -153,6 +156,10 @@
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#ContourIntegrateAdaptive">ContourIntegrateAdaptive</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#ContourIntegrateAdaptiveTransformedOdd">ContourIntegrateAdaptiveTransformedOdd</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#ContourIntegrateComposite">ContourIntegrateComposite</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#ContourIntegrateTwoPoint">ContourIntegrateTwoPoint</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#IntegrateAdaptive">IntegrateAdaptive</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#IntegrateAdaptiveTransformedOdd">IntegrateAdaptiveTransformedOdd</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm#IntegrateComposite">IntegrateComposite</a></li>
@ -167,6 +174,114 @@
<h3 class="section">Public Static Functions</h3>
<div id="ContourIntegrateAdaptive" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrateAdaptive</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.double">double</span> targetError)</h4>
<div class="content">Adaptive approximation of the definite integral in the provided interval by the trapezium rule.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span></code> f</h6>
<p class="comments">The analytic smooth complex function to integrate, define don real domain. </p>
<h6><code><span title="System.double">double</span></code> intervalBegin</h6>
<p class="comments">Where the interval starts, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> intervalEnd</h6>
<p class="comments">Where the interval stops, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> targetError</h6>
<p class="comments">The expected accuracy of the approximation. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Numerics.Complex">Complex</span></code></h6>
<p>Approximation of the finite integral in the given interval. </p>
</div>
</div>
</div>
<div id="ContourIntegrateAdaptiveTransformedOdd" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrateAdaptiveTransformedOdd</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable&lt;Double[]&gt;</span> levelAbscissas, <span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable&lt;Double[]&gt;</span> levelWeights, <span title="System.double">double</span> levelOneStep, <span title="System.double">double</span> targetRelativeError)</h4>
<div class="content">Adaptive approximation of the definite integral by the trapezium rule.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span></code> f</h6>
<p class="comments">The analytic smooth complex function to integrate, defined on the real domain. </p>
<h6><code><span title="System.double">double</span></code> intervalBegin</h6>
<p class="comments">Where the interval starts, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> intervalEnd</h6>
<p class="comments">Where the interval stops, inclusive and finite. </p>
<h6><code><span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable&lt;Double[]&gt;</span></code> levelAbscissas</h6>
<p class="comments">Abscissa vector per level provider. </p>
<h6><code><span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable&lt;Double[]&gt;</span></code> levelWeights</h6>
<p class="comments">Weight vector per level provider. </p>
<h6><code><span title="System.double">double</span></code> levelOneStep</h6>
<p class="comments">First Level Step </p>
<h6><code><span title="System.double">double</span></code> targetRelativeError</h6>
<p class="comments">The expected relative accuracy of the approximation. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Numerics.Complex">Complex</span></code></h6>
<p>Approximation of the finite integral in the given interval. </p>
</div>
</div>
</div>
<div id="ContourIntegrateComposite" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrateComposite</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.int">int</span> numberOfPartitions)</h4>
<div class="content">Composite N-point approximation of the definite integral in the provided interval by the trapezium rule.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span></code> f</h6>
<p class="comments">The analytic smooth complex function to integrate, defined on real domain. </p>
<h6><code><span title="System.double">double</span></code> intervalBegin</h6>
<p class="comments">Where the interval starts, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> intervalEnd</h6>
<p class="comments">Where the interval stops, inclusive and finite. </p>
<h6><code><span title="System.int">int</span></code> numberOfPartitions</h6>
<p class="comments">Number of composite subdivision partitions. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Numerics.Complex">Complex</span></code></h6>
<p>Approximation of the finite integral in the given interval. </p>
</div>
</div>
</div>
<div id="ContourIntegrateTwoPoint" class="method">
<h4><span title="System.Numerics.Complex">Complex</span> <strong>ContourIntegrateTwoPoint</strong>(<span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd)</h4>
<div class="content">Direct 2-point approximation of the definite integral in the provided interval by the trapezium rule.
<div class="parameters">
<h5>Parameters</h5>
<h6><code><span title="System.Func<double, Complex>">Func&lt;double, Complex&gt;</span></code> f</h6>
<p class="comments">The analytic smooth complex function to integrate, defined on real domain. </p>
<h6><code><span title="System.double">double</span></code> intervalBegin</h6>
<p class="comments">Where the interval starts, inclusive and finite. </p>
<h6><code><span title="System.double">double</span></code> intervalEnd</h6>
<p class="comments">Where the interval stops, inclusive and finite. </p>
</div>
<div class="return">
<h5>Return</h5>
<h6><code><span title="System.Numerics.Complex">Complex</span></code></h6>
<p>Approximation of the finite integral in the given interval. </p>
</div>
</div>
</div>
<div id="IntegrateAdaptive" class="method">
<h4><span title="System.double">double</span> <strong>IntegrateAdaptive</strong>(<span title="System.Func<double, double>">Func&lt;double, double&gt;</span> f, <span title="System.double">double</span> intervalBegin, <span title="System.double">double</span> intervalEnd, <span title="System.double">double</span> targetError)</h4>
<div class="content">Adaptive approximation of the definite integral in the provided interval by the trapezium rule.
@ -278,7 +393,7 @@
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@ -129,6 +129,9 @@
<ul>
<li>
<a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm">DoubleExponentialTransformation</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm">GaussKronrodRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm">GaussLegendreRule</a>
@ -218,7 +221,7 @@
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@ -128,6 +128,9 @@
<ul>
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<li>
<a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm">GaussKronrodRule</a>
</li>
<li>
<a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm">GaussLegendreRule</a>
@ -148,6 +151,7 @@
<h3 class="section">Classes</h3>
<ul>
<li><a href="../MathNet.Numerics.Integration/DoubleExponentialTransformation.htm">DoubleExponentialTransformation</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussKronrodRule.htm">GaussKronrodRule</a></li>
<li><a href="../MathNet.Numerics.Integration/GaussLegendreRule.htm">GaussLegendreRule</a></li>
<li><a href="../MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm">NewtonCotesTrapeziumRule</a></li>
<li><a href="../MathNet.Numerics.Integration/SimpsonRule.htm">SimpsonRule</a></li>
@ -155,7 +159,7 @@
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@ -443,7 +443,7 @@ The values are assumed to be sorted ascendingly by x.
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2
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@ -310,7 +310,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
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@ -492,7 +492,7 @@ and zero second derivatives at the two boundaries, sorted ascendingly by x.
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@ -303,7 +303,7 @@
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@ -388,7 +388,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
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@ -352,7 +352,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered and m
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@ -354,7 +354,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
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@ -354,7 +354,7 @@
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@ -280,8 +280,11 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
</div>
@ -289,11 +292,8 @@
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.IFormatProvider">IFormatProvider</span> provider)</h4>
<h4><span title="System.string">string</span> <strong>ToString</strong>(<span title="System.string">string</span> format)</h4>
<div class="content">
<div id="warning">
<b>Obsolete:</b> The provider argument is not used. Please use ToString().
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@ -364,7 +364,7 @@
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@ -388,7 +388,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
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@ -302,7 +302,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered and m
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@ -186,7 +186,7 @@
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@ -271,7 +271,7 @@ solution vector and x is the unknown vector.
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@ -265,7 +265,7 @@ solution vector and x is the unknown vector.
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@ -272,7 +272,7 @@ of the matrix diagonal as preconditioning values.
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@ -291,7 +291,7 @@ before switching over to the <code>BiCgStab</code> algorithm.
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@ -273,7 +273,7 @@
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@ -384,7 +384,7 @@ the preconditioner. </p>
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@ -298,7 +298,7 @@
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@ -299,7 +299,7 @@ Krylov sub-space.
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@ -265,7 +265,7 @@ solution vector and x is the unknown vector.
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@ -175,7 +175,7 @@
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@ -167,7 +167,7 @@
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@ -271,7 +271,7 @@ solution vector and x is the unknown vector.
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@ -265,7 +265,7 @@ solution vector and x is the unknown vector.
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@ -272,7 +272,7 @@ of the matrix diagonal as preconditioning values.
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