diff --git a/src/Numerics/Distributions/LogNormal.cs b/src/Numerics/Distributions/LogNormal.cs
index 4dd69055..b7d71518 100644
--- a/src/Numerics/Distributions/LogNormal.cs
+++ b/src/Numerics/Distributions/LogNormal.cs
@@ -111,6 +111,7 @@ namespace MathNet.Numerics.Distributions
/// The samples to estimate the distribution parameters from.
/// The random number generator which is used to draw random samples. Optional, can be null.
/// A log-normal distribution.
+ /// MATLAB: lognfit
public static LogNormal Estimate(IEnumerable samples, System.Random randomSource = null)
{
var muSigma2 = samples.Select(s => Math.Log(s)).MeanVariance();
@@ -302,7 +303,7 @@ namespace MathNet.Numerics.Distributions
///
/// 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.
///
/// The location at which to compute the inverse cumulative density.
/// the inverse cumulative density at .
@@ -339,6 +340,7 @@ namespace MathNet.Numerics.Distributions
/// The shape (σ) of the distribution. Range: σ ≥ 0.
/// the density at .
///
+ /// MATLAB: lognpdf
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
/// The shape (σ) of the distribution. Range: σ ≥ 0.
/// the cumulative distribution at location .
///
+ /// MATLAB: logncdf
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
///
/// 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.
///
/// The location at which to compute the inverse cumulative density.
/// The log-scale (μ) of the distribution.
/// The shape (σ) of the distribution. Range: σ ≥ 0.
/// the inverse cumulative density at .
///
+ /// MATLAB: logninv
public static double InvCDF(double mu, double sigma, double p)
{
if (sigma < 0.0) throw new ArgumentOutOfRangeException("sigma", Resources.InvalidDistributionParameters);
diff --git a/src/Numerics/Distributions/Normal.cs b/src/Numerics/Distributions/Normal.cs
index f7248882..6aa13167 100644
--- a/src/Numerics/Distributions/Normal.cs
+++ b/src/Numerics/Distributions/Normal.cs
@@ -140,6 +140,7 @@ namespace MathNet.Numerics.Distributions
/// The samples to estimate the distribution parameters from.
/// The random number generator which is used to draw random samples. Optional, can be null.
/// A normal distribution.
+ /// MATLAB: normfit
public static Normal Estimate(IEnumerable samples, System.Random randomSource = null)
{
var meanVariance = samples.MeanVariance();
@@ -311,7 +312,7 @@ namespace MathNet.Numerics.Distributions
///
/// 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.
///
/// The location at which to compute the inverse cumulative density.
/// the inverse cumulative density at .
@@ -373,6 +374,7 @@ namespace MathNet.Numerics.Distributions
/// The location at which to compute the density.
/// the density at .
///
+ /// MATLAB: normpdf
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
/// The standard deviation (σ) of the normal distribution. Range: σ ≥ 0.
/// the cumulative distribution at location .
///
+ /// MATLAB: normcdf
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
///
/// 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.
///
/// The location at which to compute the inverse cumulative density.
/// The mean (μ) of the normal distribution.
/// The standard deviation (σ) of the normal distribution. Range: σ ≥ 0.
/// the inverse cumulative density at .
///
+ /// MATLAB: norminv
public static double InvCDF(double mean, double stddev, double p)
{
if (stddev < 0.0) throw new ArgumentOutOfRangeException("stddev", Resources.InvalidDistributionParameters);