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Distributions: inline docs

optimization-1
Christoph Ruegg 13 years ago
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2e2560adb1
2 changed files with 12 additions and 4 deletions
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  1. 8
      src/Numerics/Distributions/LogNormal.cs
  2. 8
      src/Numerics/Distributions/Normal.cs

8
src/Numerics/Distributions/LogNormal.cs
View File

@ -111,6 +111,7 @@ namespace MathNet.Numerics.Distributions
/// <param name="samples">The samples to estimate the distribution parameters from.</param>
/// <param name="randomSource">The random number generator which is used to draw random samples. Optional, can be null.</param>
/// <returns>A log-normal distribution.</returns>
/// <remarks>MATLAB: lognfit</remarks>
public static LogNormal Estimate(IEnumerable<double> samples, System.Random randomSource = null)
{
var muSigma2 = samples.Select(s => Math.Log(s)).MeanVariance();
@ -302,7 +303,7 @@ namespace MathNet.Numerics.Distributions
/// <summary>
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the 'quantile function'.
/// at the given probability. This is also known as the quantile or percent point function.
/// </summary>
/// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
@ -339,6 +340,7 @@ namespace MathNet.Numerics.Distributions
/// <param name="sigma">The shape (σ) of the distribution. Range: σ ≥ 0.</param>
/// <returns>the density at <paramref name="x"/>.</returns>
/// <seealso cref="Density"/>
/// <remarks>MATLAB: lognpdf</remarks>
public static double PDF(double mu, double sigma, double x)
{
if (sigma < 0.0) throw new ArgumentOutOfRangeException("sigma", Resources.InvalidDistributionParameters);
@ -381,6 +383,7 @@ namespace MathNet.Numerics.Distributions
/// <param name="sigma">The shape (σ) of the distribution. Range: σ ≥ 0.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CumulativeDistribution"/>
/// <remarks>MATLAB: logncdf</remarks>
public static double CDF(double mu, double sigma, double x)
{
if (sigma < 0.0) throw new ArgumentOutOfRangeException("sigma", Resources.InvalidDistributionParameters);
@ -391,13 +394,14 @@ namespace MathNet.Numerics.Distributions
/// <summary>
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the 'quantile function'.
/// at the given probability. This is also known as the quantile or percent point function.
/// </summary>
/// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <param name="mu">The log-scale (μ) of the distribution.</param>
/// <param name="sigma">The shape (σ) of the distribution. Range: σ ≥ 0.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
/// <seealso cref="InverseCumulativeDistribution"/>
/// <remarks>MATLAB: logninv</remarks>
public static double InvCDF(double mu, double sigma, double p)
{
if (sigma < 0.0) throw new ArgumentOutOfRangeException("sigma", Resources.InvalidDistributionParameters);

8
src/Numerics/Distributions/Normal.cs
View File

@ -140,6 +140,7 @@ namespace MathNet.Numerics.Distributions
/// <param name="samples">The samples to estimate the distribution parameters from.</param>
/// <param name="randomSource">The random number generator which is used to draw random samples. Optional, can be null.</param>
/// <returns>A normal distribution.</returns>
/// <remarks>MATLAB: normfit</remarks>
public static Normal Estimate(IEnumerable<double> samples, System.Random randomSource = null)
{
var meanVariance = samples.MeanVariance();
@ -311,7 +312,7 @@ namespace MathNet.Numerics.Distributions
/// <summary>
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the 'quantile function'.
/// at the given probability. This is also known as the quantile or percent point function.
/// </summary>
/// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
@ -373,6 +374,7 @@ namespace MathNet.Numerics.Distributions
/// <param name="x">The location at which to compute the density.</param>
/// <returns>the density at <paramref name="x"/>.</returns>
/// <seealso cref="Density"/>
/// <remarks>MATLAB: normpdf</remarks>
public static double PDF(double mean, double stddev, double x)
{
if (stddev < 0.0) throw new ArgumentOutOfRangeException("stddev", Resources.InvalidDistributionParameters);
@ -405,6 +407,7 @@ namespace MathNet.Numerics.Distributions
/// <param name="stddev">The standard deviation (σ) of the normal distribution. Range: σ ≥ 0.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CumulativeDistribution"/>
/// <remarks>MATLAB: normcdf</remarks>
public static double CDF(double mean, double stddev, double x)
{
if (stddev < 0.0) throw new ArgumentOutOfRangeException("stddev", Resources.InvalidDistributionParameters);
@ -414,13 +417,14 @@ namespace MathNet.Numerics.Distributions
/// <summary>
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the 'quantile function'.
/// at the given probability. This is also known as the quantile or percent point function.
/// </summary>
/// <param name="p">The location at which to compute the inverse cumulative density.</param>
/// <param name="mean">The mean (μ) of the normal distribution.</param>
/// <param name="stddev">The standard deviation (σ) of the normal distribution. Range: σ ≥ 0.</param>
/// <returns>the inverse cumulative density at <paramref name="p"/>.</returns>
/// <seealso cref="InverseCumulativeDistribution"/>
/// <remarks>MATLAB: norminv</remarks>
public static double InvCDF(double mean, double stddev, double p)
{
if (stddev < 0.0) throw new ArgumentOutOfRangeException("stddev", Resources.InvalidDistributionParameters);

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