diff --git a/src/Numerics/Distributions/Bernoulli.cs b/src/Numerics/Distributions/Bernoulli.cs index cec06831..89f8c3c8 100644 --- a/src/Numerics/Distributions/Bernoulli.cs +++ b/src/Numerics/Distributions/Bernoulli.cs @@ -41,11 +41,6 @@ namespace MathNet.Numerics.Distributions /// p specifies the probability that a 1 is generated. /// Wikipedia - Bernoulli distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Bernoulli : IDiscreteDistribution { System.Random _random; @@ -85,7 +80,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The probability (p) of generating one. Range: 0 ≤ p ≤ 1. /// true when the parameters are valid, false otherwise. diff --git a/src/Numerics/Distributions/Beta.cs b/src/Numerics/Distributions/Beta.cs index 1ea2ee4d..38a4cd50 100644 --- a/src/Numerics/Distributions/Beta.cs +++ b/src/Numerics/Distributions/Beta.cs @@ -37,21 +37,17 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Beta distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Beta distribution. /// /// - /// There are a few special cases for the parameterization of the Beta distribution. When both + /// There are a few special cases for the parameterization of the Beta distribution. When both /// shape parameters are positive infinity, the Beta distribution degenerates to a point distribution /// at 0.5. When one of the shape parameters is positive infinity, the distribution degenerates to a point - /// distribution at the positive infinity. When both shape parameters are 0.0, the Beta distribution + /// distribution at the positive infinity. When both shape parameters are 0.0, the Beta distribution /// degenerates to a Bernoulli distribution with parameter 0.5. When one shape parameter is 0.0, the - /// distribution degenerates to a point distribution at the non-zero shape parameter. - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. + /// distribution degenerates to a point distribution at the non-zero shape parameter. + /// public class Beta : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/Binomial.cs b/src/Numerics/Distributions/Binomial.cs index 241aa104..adfd5446 100644 --- a/src/Numerics/Distributions/Binomial.cs +++ b/src/Numerics/Distributions/Binomial.cs @@ -37,15 +37,12 @@ namespace MathNet.Numerics.Distributions { /// /// Discrete Univariate Binomial distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Binomial distribution. /// - /// The distribution is parameterized by a probability (between 0.0 and 1.0). - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. + /// + /// The distribution is parameterized by a probability (between 0.0 and 1.0). + /// public class Binomial : IDiscreteDistribution { System.Random _random; @@ -90,7 +87,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The success probability (p) in each trial. Range: 0 ≤ p ≤ 1. /// The number of trials (n). Range: n ≥ 0. diff --git a/src/Numerics/Distributions/Categorical.cs b/src/Numerics/Distributions/Categorical.cs index 3e19db09..7c837c6f 100644 --- a/src/Numerics/Distributions/Categorical.cs +++ b/src/Numerics/Distributions/Categorical.cs @@ -39,18 +39,15 @@ namespace MathNet.Numerics.Distributions { /// /// Discrete Univariate Categorical distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Categorical distribution. This /// distribution is sometimes called the Discrete distribution. /// - /// The distribution is parameterized by a vector of ratios: in other words, the parameter + /// + /// The distribution is parameterized by a vector of ratios: in other words, the parameter /// does not have to be normalized and sum to 1. The reason is that some vectors can't be exactly normalized - /// to sum to 1 in floating point representation. - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. + /// to sum to 1 in floating point representation. + /// public class Categorical : IDiscreteDistribution { System.Random _random; @@ -61,7 +58,7 @@ namespace MathNet.Numerics.Distributions /// /// Initializes a new instance of the Categorical class. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// If any of the probabilities are negative or do not sum to one. public Categorical(double[] probabilityMass) @@ -73,7 +70,7 @@ namespace MathNet.Numerics.Distributions /// /// Initializes a new instance of the Categorical class. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The random number generator which is used to draw random samples. /// If any of the probabilities are negative or do not sum to one. @@ -84,7 +81,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the Categorical class from a . The distribution + /// Initializes a new instance of the Categorical class from a . The distribution /// will not be automatically updated when the histogram changes. The categorical distribution will have /// one value for each bucket and a probability for that value proportional to the bucket count. /// @@ -119,7 +116,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic. /// If any of the probabilities are negative returns false, or if the sum of parameters is 0.0; otherwise true @@ -141,7 +138,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic. /// If any of the probabilities are negative returns false, or if the sum of parameters is 0.0; otherwise true @@ -165,7 +162,7 @@ namespace MathNet.Numerics.Distributions /// /// Sets the parameters of the distribution after checking their validity. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// When the parameters are out of range. void SetParameters(double[] p) @@ -401,7 +398,7 @@ namespace MathNet.Numerics.Distributions /// Computes the cumulative distribution function. This method performs no parameter checking. /// If the probability mass was normalized, the resulting cumulative distribution is normalized as well (up to numerical errors). /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// An array representing the unnormalized cumulative distribution function. internal static double[] ProbabilityMassToCumulativeDistribution(double[] pmfUnnormalized) diff --git a/src/Numerics/Distributions/Cauchy.cs b/src/Numerics/Distributions/Cauchy.cs index 95bca0c5..6d86338d 100644 --- a/src/Numerics/Distributions/Cauchy.cs +++ b/src/Numerics/Distributions/Cauchy.cs @@ -37,14 +37,9 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Cauchy distribution. - /// The Cauchy distribution is a symmetric continuous probability distribution. For details about this distribution, see + /// The Cauchy distribution is a symmetric continuous probability distribution. For details about this distribution, see /// Wikipedia - Cauchy distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Cauchy : IContinuousDistribution { System.Random _random; @@ -60,7 +55,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The location (x0) of the distribution. /// The scale (γ) of the distribution. Range: γ > 0. @@ -71,7 +66,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The location (x0) of the distribution. /// The scale (γ) of the distribution. Range: γ > 0. diff --git a/src/Numerics/Distributions/Chi.cs b/src/Numerics/Distributions/Chi.cs index 2d795dc9..ec4441d5 100644 --- a/src/Numerics/Distributions/Chi.cs +++ b/src/Numerics/Distributions/Chi.cs @@ -37,16 +37,11 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Chi distribution. - /// This distribution is a continuous probability distribution. The distribution usually arises when a k-dimensional vector's orthogonal - /// components are independent and each follow a standard normal distribution. The length of the vector will + /// This distribution is a continuous probability distribution. The distribution usually arises when a k-dimensional vector's orthogonal + /// components are independent and each follow a standard normal distribution. The length of the vector will /// then have a chi distribution. /// Wikipedia - Chi distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Chi : IContinuousDistribution { System.Random _random; @@ -54,7 +49,7 @@ namespace MathNet.Numerics.Distributions double _freedom; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degrees of freedom (k) of the distribution. Range: k > 0. public Chi(double freedom) @@ -64,7 +59,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degrees of freedom (k) of the distribution. Range: k > 0. /// The random number generator which is used to draw random samples. diff --git a/src/Numerics/Distributions/ChiSquared.cs b/src/Numerics/Distributions/ChiSquared.cs index fafa7af0..35780c25 100644 --- a/src/Numerics/Distributions/ChiSquared.cs +++ b/src/Numerics/Distributions/ChiSquared.cs @@ -40,11 +40,6 @@ namespace MathNet.Numerics.Distributions /// This distribution is a sum of the squares of k independent standard normal random variables. /// Wikipedia - ChiSquare distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class ChiSquared : IContinuousDistribution { System.Random _random; @@ -52,7 +47,7 @@ namespace MathNet.Numerics.Distributions double _freedom; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degrees of freedom (k) of the distribution. Range: k > 0. public ChiSquared(double freedom) @@ -62,7 +57,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degrees of freedom (k) of the distribution. Range: k > 0. /// The random number generator which is used to draw random samples. diff --git a/src/Numerics/Distributions/ContinuousUniform.cs b/src/Numerics/Distributions/ContinuousUniform.cs index cadef445..36c8d935 100644 --- a/src/Numerics/Distributions/ContinuousUniform.cs +++ b/src/Numerics/Distributions/ContinuousUniform.cs @@ -37,14 +37,9 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Uniform distribution. - /// The continuous uniform distribution is a distribution over real numbers. For details about this distribution, see + /// The continuous uniform distribution is a distribution over real numbers. For details about this distribution, see /// Wikipedia - Continuous uniform distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class ContinuousUniform : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/ConwayMaxwellPoisson.cs b/src/Numerics/Distributions/ConwayMaxwellPoisson.cs index fbff7995..96c37876 100644 --- a/src/Numerics/Distributions/ConwayMaxwellPoisson.cs +++ b/src/Numerics/Distributions/ConwayMaxwellPoisson.cs @@ -39,7 +39,7 @@ namespace MathNet.Numerics.Distributions /// Discrete Univariate Conway-Maxwell-Poisson distribution. /// The Conway-Maxwell-Poisson distribution is a generalization of the Poisson, Geometric and Bernoulli /// distributions. It is parameterized by two real numbers "lambda" and "nu". For - /// + /// /// nu = 0 the distribution reverts to a Geometric distribution /// nu = 1 the distribution reverts to the Poisson distribution /// nu -> infinity the distribution converges to a Bernoulli distribution @@ -47,11 +47,6 @@ namespace MathNet.Numerics.Distributions /// This implementation will cache the value of the normalization constant. /// Wikipedia - ConwayMaxwellPoisson distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class ConwayMaxwellPoisson : IDiscreteDistribution { System.Random _random; @@ -81,7 +76,7 @@ namespace MathNet.Numerics.Distributions const double Tolerance = 1e-12; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The lambda (λ) parameter. Range: λ > 0. /// The rate of decay (ν) parameter. Range: ν ≥ 0. @@ -92,7 +87,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The lambda (λ) parameter. Range: λ > 0. /// The rate of decay (ν) parameter. Range: ν ≥ 0. @@ -113,7 +108,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The lambda (λ) parameter. Range: λ > 0. /// The rate of decay (ν) parameter. Range: ν ≥ 0. diff --git a/src/Numerics/Distributions/Dirichlet.cs b/src/Numerics/Distributions/Dirichlet.cs index f72d2a9e..fd48cd94 100644 --- a/src/Numerics/Distributions/Dirichlet.cs +++ b/src/Numerics/Distributions/Dirichlet.cs @@ -36,14 +36,9 @@ using MathNet.Numerics.Random; namespace MathNet.Numerics.Distributions { /// - /// Multivariate Dirichlet distribution. For details about this distribution, see + /// Multivariate Dirichlet distribution. For details about this distribution, see /// Wikipedia - Dirichlet distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Dirichlet : IDistribution { System.Random _random; @@ -74,7 +69,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// random number generator. /// The value of each parameter of the Dirichlet distribution. /// The dimension of the Dirichlet distribution. @@ -92,7 +87,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// random number generator. /// The value of each parameter of the Dirichlet distribution. /// The dimension of the Dirichlet distribution. @@ -252,7 +247,7 @@ namespace MathNet.Numerics.Distributions /// /// The locations at which to compute the density. /// the density at . - /// The Dirichlet distribution requires that the sum of the components of x equals 1. + /// The Dirichlet distribution requires that the sum of the components of x equals 1. /// You can also leave out the last component, and it will be computed from the others. public double Density(double[] x) { diff --git a/src/Numerics/Distributions/DiscreteUniform.cs b/src/Numerics/Distributions/DiscreteUniform.cs index 5f6e9f21..b9355fd1 100644 --- a/src/Numerics/Distributions/DiscreteUniform.cs +++ b/src/Numerics/Distributions/DiscreteUniform.cs @@ -41,11 +41,6 @@ namespace MathNet.Numerics.Distributions /// is parameterized by a lower and upper bound (both inclusive). /// Wikipedia - Discrete uniform distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class DiscreteUniform : IDiscreteDistribution { System.Random _random; @@ -88,7 +83,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// Lower bound. Range: lower ≤ upper. /// Upper bound. Range: lower ≤ upper. diff --git a/src/Numerics/Distributions/Erlang.cs b/src/Numerics/Distributions/Erlang.cs index f5e64604..82401fda 100644 --- a/src/Numerics/Distributions/Erlang.cs +++ b/src/Numerics/Distributions/Erlang.cs @@ -41,11 +41,6 @@ namespace MathNet.Numerics.Distributions /// relation to the exponential and Gamma distributions. /// Wikipedia - Erlang distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Erlang : IContinuousDistribution { System.Random _random; @@ -54,7 +49,7 @@ namespace MathNet.Numerics.Distributions double _rate; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The shape (k) of the Erlang distribution. Range: k ≥ 0. /// The rate or inverse scale (λ) of the Erlang distribution. Range: λ ≥ 0. @@ -65,7 +60,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The shape (k) of the Erlang distribution. Range: k ≥ 0. /// The rate or inverse scale (λ) of the Erlang distribution. Range: λ ≥ 0. diff --git a/src/Numerics/Distributions/Exponential.cs b/src/Numerics/Distributions/Exponential.cs index eb404bef..95639a02 100644 --- a/src/Numerics/Distributions/Exponential.cs +++ b/src/Numerics/Distributions/Exponential.cs @@ -40,11 +40,6 @@ namespace MathNet.Numerics.Distributions /// The exponential distribution is a distribution over the real numbers parameterized by one non-negative parameter. /// Wikipedia - exponential distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Exponential : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/FisherSnedecor.cs b/src/Numerics/Distributions/FisherSnedecor.cs index 403ec4d3..4fe5947e 100644 --- a/src/Numerics/Distributions/FisherSnedecor.cs +++ b/src/Numerics/Distributions/FisherSnedecor.cs @@ -37,14 +37,9 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate F-distribution, also known as Fisher-Snedecor distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - FisherSnedecor distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class FisherSnedecor : IContinuousDistribution { System.Random _random; @@ -53,7 +48,7 @@ namespace MathNet.Numerics.Distributions double _freedom2; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The first degree of freedom (d1) of the distribution. Range: d1 > 0. /// The second degree of freedom (d2) of the distribution. Range: d2 > 0. @@ -64,7 +59,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The first degree of freedom (d1) of the distribution. Range: d1 > 0. /// The second degree of freedom (d2) of the distribution. Range: d2 > 0. diff --git a/src/Numerics/Distributions/Gamma.cs b/src/Numerics/Distributions/Gamma.cs index bcb73daa..734b1e4e 100644 --- a/src/Numerics/Distributions/Gamma.cs +++ b/src/Numerics/Distributions/Gamma.cs @@ -37,22 +37,19 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Gamma distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Gamma distribution. /// /// - /// The Gamma distribution is parametrized by a shape and inverse scale parameter. When we want + /// The Gamma distribution is parametrized by a shape and inverse scale parameter. When we want /// to specify a Gamma distribution which is a point distribution we set the shape parameter to be the /// location of the point distribution and the inverse scale as positive infinity. The distribution - /// with shape and inverse scale both zero is undefined. - /// Random number generation for the Gamma distribution is based on the algorithm in: + /// with shape and inverse scale both zero is undefined. + /// + /// Random number generation for the Gamma distribution is based on the algorithm in: /// "A Simple Method for Generating Gamma Variables" - Marsaglia & Tsang - /// ACM Transactions on Mathematical Software, Vol. 26, No. 3, September 2000, Pages 363–372. - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. + /// ACM Transactions on Mathematical Software, Vol. 26, No. 3, September 2000, Pages 363–372. + /// public class Gamma : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/Geometric.cs b/src/Numerics/Distributions/Geometric.cs index 7725ff72..dd9c3a44 100644 --- a/src/Numerics/Distributions/Geometric.cs +++ b/src/Numerics/Distributions/Geometric.cs @@ -41,11 +41,6 @@ namespace MathNet.Numerics.Distributions /// This implementation of the Geometric distribution will never generate 0's. /// Wikipedia - geometric distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Geometric : IDiscreteDistribution { System.Random _random; @@ -83,7 +78,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The probability (p) of generating one. Range: 0 ≤ p ≤ 1. /// true when the parameters are valid, false otherwise. diff --git a/src/Numerics/Distributions/Hypergeometric.cs b/src/Numerics/Distributions/Hypergeometric.cs index 3be4d4be..156f8742 100644 --- a/src/Numerics/Distributions/Hypergeometric.cs +++ b/src/Numerics/Distributions/Hypergeometric.cs @@ -37,17 +37,11 @@ namespace MathNet.Numerics.Distributions { /// /// Discrete Univariate Hypergeometric distribution. - /// This distribution is a discrete probability distribution that describes the number of successes in a sequence - /// of n draws from a finite population without replacement, just as the binomial distribution + /// This distribution is a discrete probability distribution that describes the number of successes in a sequence + /// of n draws from a finite population without replacement, just as the binomial distribution /// describes the number of successes for draws with replacement /// Wikipedia - Hypergeometric distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Hypergeometric : IDiscreteDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/InverseGamma.cs b/src/Numerics/Distributions/InverseGamma.cs index 5590b872..0629d991 100644 --- a/src/Numerics/Distributions/InverseGamma.cs +++ b/src/Numerics/Distributions/InverseGamma.cs @@ -42,11 +42,6 @@ namespace MathNet.Numerics.Distributions /// two positive parameters. /// Wikipedia - InverseGamma distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class InverseGamma : IContinuousDistribution { System.Random _random; @@ -55,7 +50,7 @@ namespace MathNet.Numerics.Distributions double _scale; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The shape (α) of the distribution. Range: α > 0. /// The scale (β) of the distribution. Range: β > 0. @@ -66,7 +61,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The shape (α) of the distribution. Range: α > 0. /// The scale (β) of the distribution. Range: β > 0. diff --git a/src/Numerics/Distributions/InverseWishart.cs b/src/Numerics/Distributions/InverseWishart.cs index be9b98aa..5e9142f5 100644 --- a/src/Numerics/Distributions/InverseWishart.cs +++ b/src/Numerics/Distributions/InverseWishart.cs @@ -42,11 +42,6 @@ namespace MathNet.Numerics.Distributions /// is the conjugate prior for the covariance matrix of a multivariate normal distribution. /// Wikipedia - Inverse-Wishart distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class InverseWishart : IDistribution { System.Random _random; @@ -60,7 +55,7 @@ namespace MathNet.Numerics.Distributions Cholesky _chol; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degree of freedom (ν) for the inverse Wishart distribution. /// The scale matrix (Ψ) for the inverse Wishart distribution. @@ -71,7 +66,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degree of freedom (ν) for the inverse Wishart distribution. /// The scale matrix (Ψ) for the inverse Wishart distribution. @@ -92,7 +87,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The degree of freedom (ν) for the inverse Wishart distribution. /// The scale matrix (Ψ) for the inverse Wishart distribution. diff --git a/src/Numerics/Distributions/Laplace.cs b/src/Numerics/Distributions/Laplace.cs index 3daa4f04..034ae1c5 100644 --- a/src/Numerics/Distributions/Laplace.cs +++ b/src/Numerics/Distributions/Laplace.cs @@ -42,11 +42,6 @@ namespace MathNet.Numerics.Distributions /// p(x) = \frac{1}{2 * scale} \exp{- |x - mean| / scale}. /// Wikipedia - Laplace distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Laplace : IContinuousDistribution { System.Random _random; @@ -55,7 +50,7 @@ namespace MathNet.Numerics.Distributions double _scale; /// - /// Initializes a new instance of the class (location = 0, scale = 1). + /// Initializes a new instance of the class (location = 0, scale = 1). /// public Laplace() : this(0.0, 1.0) @@ -63,7 +58,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The location (μ) of the distribution. /// The scale (b) of the distribution. Range: b > 0. @@ -75,7 +70,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The location (μ) of the distribution. /// The scale (b) of the distribution. Range: b > 0. diff --git a/src/Numerics/Distributions/LogNormal.cs b/src/Numerics/Distributions/LogNormal.cs index 32625670..17022903 100644 --- a/src/Numerics/Distributions/LogNormal.cs +++ b/src/Numerics/Distributions/LogNormal.cs @@ -39,14 +39,9 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Log-Normal distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Log-Normal distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class LogNormal : IContinuousDistribution { System.Random _random; @@ -55,7 +50,7 @@ namespace MathNet.Numerics.Distributions double _sigma; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// The distribution will be initialized with the default /// random number generator. /// @@ -68,7 +63,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// The distribution will be initialized with the default /// random number generator. /// diff --git a/src/Numerics/Distributions/MatrixNormal.cs b/src/Numerics/Distributions/MatrixNormal.cs index 4f2fb515..bfaece86 100644 --- a/src/Numerics/Distributions/MatrixNormal.cs +++ b/src/Numerics/Distributions/MatrixNormal.cs @@ -42,17 +42,12 @@ namespace MathNet.Numerics.Distributions /// for the columns (K). If the dimension of M is d-by-m then V is d-by-d and K is m-by-m. /// Wikipedia - MatrixNormal distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class MatrixNormal : IDistribution { System.Random _random; /// - /// The mean of the matrix normal distribution. + /// The mean of the matrix normal distribution. /// Matrix _m; @@ -67,7 +62,7 @@ namespace MathNet.Numerics.Distributions Matrix _k; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The mean of the matrix normal. /// The covariance matrix for the rows. @@ -80,7 +75,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The mean of the matrix normal. /// The covariance matrix for the rows. @@ -105,7 +100,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The mean of the matrix normal. /// The covariance matrix for the rows. diff --git a/src/Numerics/Distributions/Multinomial.cs b/src/Numerics/Distributions/Multinomial.cs index 143f764c..606ae4da 100644 --- a/src/Numerics/Distributions/Multinomial.cs +++ b/src/Numerics/Distributions/Multinomial.cs @@ -40,17 +40,14 @@ using MathNet.Numerics.Statistics; namespace MathNet.Numerics.Distributions { /// - /// Multivariate Multinomial distribution. For details about this distribution, see + /// Multivariate Multinomial distribution. For details about this distribution, see /// Wikipedia - Multinomial distribution. /// - /// The distribution is parameterized by a vector of ratios: in other words, the parameter + /// + /// The distribution is parameterized by a vector of ratios: in other words, the parameter /// does not have to be normalized and sum to 1. The reason is that some vectors can't be exactly normalized - /// to sum to 1 in floating point representation. - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. + /// to sum to 1 in floating point representation. + /// public class Multinomial : IDistribution { System.Random _random; @@ -68,7 +65,7 @@ namespace MathNet.Numerics.Distributions /// /// Initializes a new instance of the Multinomial class. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The number of trials. /// If any of the probabilities are negative or do not sum to one. @@ -82,7 +79,7 @@ namespace MathNet.Numerics.Distributions /// /// Initializes a new instance of the Multinomial class. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The number of trials. /// The random number generator which is used to draw random samples. @@ -132,12 +129,12 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The number of trials. - /// If any of the probabilities are negative returns false, + /// If any of the probabilities are negative returns false, /// if the sum of parameters is 0.0, or if the number of trials is negative; otherwise true. static bool IsValidParameterSet(IEnumerable p, int n) { @@ -163,7 +160,7 @@ namespace MathNet.Numerics.Distributions /// /// Sets the parameters of the distribution after checking their validity. /// - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The number of trials. /// When the parameters are out of range. @@ -220,7 +217,7 @@ namespace MathNet.Numerics.Distributions { get { - // Do not use _p, because operations below will modify _p array. Use P or _p.Clone(). + // Do not use _p, because operations below will modify _p array. Use P or _p.Clone(). var res = (DenseVector) P; for (var i = 0; i < res.Count; i++) { @@ -238,7 +235,7 @@ namespace MathNet.Numerics.Distributions { get { - // Do not use _p, because operations below will modify _p array. Use P or _p.Clone(). + // Do not use _p, because operations below will modify _p array. Use P or _p.Clone(). var res = (DenseVector) P; for (var i = 0; i < res.Count; i++) { @@ -337,7 +334,7 @@ namespace MathNet.Numerics.Distributions /// Samples one multinomial distributed random variable. /// /// The random number generator to use. - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The number of trials. /// the counts for each of the different possible values. @@ -366,7 +363,7 @@ namespace MathNet.Numerics.Distributions /// Samples a multinomially distributed random variable. /// /// The random number generator to use. - /// An array of nonnegative ratios: this array does not need to be normalized + /// An array of nonnegative ratios: this array does not need to be normalized /// as this is often impossible using floating point arithmetic. /// The number of variables needed. /// a sequence of counts for each of the different possible values. diff --git a/src/Numerics/Distributions/NegativeBinomial.cs b/src/Numerics/Distributions/NegativeBinomial.cs index 5bd187c9..ad8bb6f2 100644 --- a/src/Numerics/Distributions/NegativeBinomial.cs +++ b/src/Numerics/Distributions/NegativeBinomial.cs @@ -42,11 +42,6 @@ namespace MathNet.Numerics.Distributions /// when the probability of head is p. /// Wikipedia - NegativeBinomial distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class NegativeBinomial : IDiscreteDistribution { System.Random _random; @@ -55,7 +50,7 @@ namespace MathNet.Numerics.Distributions double _p; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The number of failures (r) until the experiment stopped. Range: r ≥ 0. /// The probability (p) of a trial resulting in success. Range: 0 ≤ p ≤ 1. @@ -66,7 +61,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The number of failures (r) until the experiment stopped. Range: r ≥ 0. /// The probability (p) of a trial resulting in success. Range: 0 ≤ p ≤ 1. @@ -89,11 +84,11 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The number of failures (r) until the experiment stopped. Range: r ≥ 0. /// The probability (p) of a trial resulting in success. Range: 0 ≤ p ≤ 1. - /// true when the parameters are valid, false otherwise. + /// true when the parameters are valid, false otherwise. static bool IsValidParameterSet(double r, double p) { return r >= 0.0 && p >= 0.0 && p <= 1.0; diff --git a/src/Numerics/Distributions/Normal.cs b/src/Numerics/Distributions/Normal.cs index 9086a369..302da462 100644 --- a/src/Numerics/Distributions/Normal.cs +++ b/src/Numerics/Distributions/Normal.cs @@ -38,14 +38,9 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Normal distribution, also known as Gaussian distribution. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Normal distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Normal : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/NormalGamma.cs b/src/Numerics/Distributions/NormalGamma.cs index 25bc75f9..213f744f 100644 --- a/src/Numerics/Distributions/NormalGamma.cs +++ b/src/Numerics/Distributions/NormalGamma.cs @@ -52,7 +52,7 @@ namespace MathNet.Numerics.Distributions double _precision; /// - /// Initializes a new instance of the struct. + /// Initializes a new instance of the struct. /// /// The mean of the pair. /// The precision of the pair. @@ -96,11 +96,6 @@ namespace MathNet.Numerics.Distributions /// will be positive infinity. A completely degenerate NormalGamma distribution with known mean and precision is possible as well. /// Wikipedia - Normal-Gamma distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class NormalGamma : IDistribution { System.Random _random; @@ -111,7 +106,7 @@ namespace MathNet.Numerics.Distributions double _precisionInvScale; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The location of the mean. /// The scale of the mean. @@ -124,7 +119,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The location of the mean. /// The scale of the mean. @@ -148,7 +143,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The location of the mean. /// The scale of the mean. diff --git a/src/Numerics/Distributions/Pareto.cs b/src/Numerics/Distributions/Pareto.cs index 79851be1..0092304b 100644 --- a/src/Numerics/Distributions/Pareto.cs +++ b/src/Numerics/Distributions/Pareto.cs @@ -37,16 +37,11 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Pareto distribution. - /// The Pareto distribution is a power law probability distribution that coincides with social, + /// The Pareto distribution is a power law probability distribution that coincides with social, /// scientific, geophysical, actuarial, and many other types of observable phenomena. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Pareto distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Pareto : IContinuousDistribution { System.Random _random; @@ -55,7 +50,7 @@ namespace MathNet.Numerics.Distributions double _shape; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The scale (xm) of the distribution. Range: xm > 0. /// The shape (α) of the distribution. Range: α > 0. @@ -67,7 +62,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The scale (xm) of the distribution. Range: xm > 0. /// The shape (α) of the distribution. Range: α > 0. diff --git a/src/Numerics/Distributions/Rayleigh.cs b/src/Numerics/Distributions/Rayleigh.cs index bbe53fec..ea9fdc6f 100644 --- a/src/Numerics/Distributions/Rayleigh.cs +++ b/src/Numerics/Distributions/Rayleigh.cs @@ -37,17 +37,12 @@ namespace MathNet.Numerics.Distributions { /// /// Continuous Univariate Rayleigh distribution. - /// The Rayleigh distribution (pronounced /ˈreɪli/) is a continuous probability distribution. As an - /// example of how it arises, the wind speed will have a Rayleigh distribution if the components of + /// The Rayleigh distribution (pronounced /ˈreɪli/) is a continuous probability distribution. As an + /// example of how it arises, the wind speed will have a Rayleigh distribution if the components of /// the two-dimensional wind velocity vector are uncorrelated and normally distributed with equal variance. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Rayleigh distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Rayleigh : IContinuousDistribution { System.Random _random; @@ -55,7 +50,7 @@ namespace MathNet.Numerics.Distributions double _scale; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The scale (σ) of the distribution. Range: σ > 0. /// If is negative. @@ -66,7 +61,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The scale (σ) of the distribution. Range: σ > 0. /// The random number generator which is used to draw random samples. diff --git a/src/Numerics/Distributions/Stable.cs b/src/Numerics/Distributions/Stable.cs index fabf1f8f..25a251c2 100644 --- a/src/Numerics/Distributions/Stable.cs +++ b/src/Numerics/Distributions/Stable.cs @@ -43,11 +43,6 @@ namespace MathNet.Numerics.Distributions /// For details about this distribution, see /// Wikipedia - Stable distribution. /// - /// The distribution will use the by default.` - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Stable : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/Weibull.cs b/src/Numerics/Distributions/Weibull.cs index b779e8ca..87861cd5 100644 --- a/src/Numerics/Distributions/Weibull.cs +++ b/src/Numerics/Distributions/Weibull.cs @@ -41,12 +41,8 @@ namespace MathNet.Numerics.Distributions /// Wikipedia - Weibull distribution. /// /// - /// The Weibull distribution is parametrized by a shape and scale parameter. - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. + /// The Weibull distribution is parametrized by a shape and scale parameter. + /// public class Weibull : IContinuousDistribution { System.Random _random; diff --git a/src/Numerics/Distributions/Wishart.cs b/src/Numerics/Distributions/Wishart.cs index 00186d60..9714262d 100644 --- a/src/Numerics/Distributions/Wishart.cs +++ b/src/Numerics/Distributions/Wishart.cs @@ -44,11 +44,6 @@ namespace MathNet.Numerics.Distributions /// normal distribution. /// Wikipedia - Wishart distribution. /// - /// The distribution will use the by default. - /// Users can set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Wishart : IDistribution { System.Random _random; @@ -69,7 +64,7 @@ namespace MathNet.Numerics.Distributions Cholesky _chol; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degrees of freedom (n) for the Wishart distribution. /// The scale matrix (V) for the Wishart distribution. @@ -80,7 +75,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The degrees of freedom (n) for the Wishart distribution. /// The scale matrix (V) for the Wishart distribution. @@ -110,7 +105,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The degrees of freedom (n) for the Wishart distribution. /// The scale matrix (V) for the Wishart distribution. diff --git a/src/Numerics/Distributions/Zipf.cs b/src/Numerics/Distributions/Zipf.cs index 28034add..5f1aa397 100644 --- a/src/Numerics/Distributions/Zipf.cs +++ b/src/Numerics/Distributions/Zipf.cs @@ -37,17 +37,12 @@ namespace MathNet.Numerics.Distributions { /// /// Discrete Univariate Zipf distribution. - /// Zipf's law, an empirical law formulated using mathematical statistics, refers to the fact - /// that many types of data studied in the physical and social sciences can be approximated with + /// Zipf's law, an empirical law formulated using mathematical statistics, refers to the fact + /// that many types of data studied in the physical and social sciences can be approximated with /// a Zipfian distribution, one of a family of related discrete power law probability distributions. - /// For details about this distribution, see + /// For details about this distribution, see /// Wikipedia - Zipf distribution. /// - /// The distribution will use the by default. - /// Users can get/set the random number generator by using the property. - /// The statistics classes will check all the incoming parameters whether they are in the allowed - /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters - /// to false, all parameter checks can be turned off. public class Zipf : IDiscreteDistribution { System.Random _random; @@ -63,7 +58,7 @@ namespace MathNet.Numerics.Distributions int _n; /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The s parameter of the distribution. /// The n parameter of the distribution. @@ -74,7 +69,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Initializes a new instance of the class. + /// Initializes a new instance of the class. /// /// The s parameter of the distribution. /// The n parameter of the distribution. @@ -95,7 +90,7 @@ namespace MathNet.Numerics.Distributions } /// - /// Checks whether the parameters of the distribution are valid. + /// Checks whether the parameters of the distribution are valid. /// /// The s parameter of the distribution. /// The n parameter of the distribution.