Namespaces

Types in MathNet.Numerics.Distributions

Type LogNormal

Namespace MathNet.Numerics.Distributions

Interfaces IContinuousDistribution

Continuous Univariate Log-Normal distribution. For details about this distribution, see.

Constructors

Static Functions

Methods

Properties

Public Constructors

LogNormal(double mu, double sigma, Random randomSource)

Initializes a new instance of the LogNormal class. The distribution will be initialized with the default random number generator.
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Random randomSource

The random number generator which is used to draw random samples.

LogNormal(double mu, double sigma)

Initializes a new instance of the LogNormal class. The distribution will be initialized with the default random number generator.
Parameters
double mu

The log-scale (μ) of the logarithm of the distribution.

double sigma

The shape (σ) of the logarithm of the distribution. Range: σ ≥ 0.

Public Static Functions

double CDF(double mu, double sigma, double x)

Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
MATLAB: logncdf
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

double x

The location at which to compute the cumulative distribution function.

Return
double

the cumulative distribution at location x.

LogNormal Estimate(IEnumerable<double> samples, Random randomSource)

Estimates the log-normal distribution parameters from sample data with maximum-likelihood.
MATLAB: lognfit
Parameters
IEnumerable<double> samples

The samples to estimate the distribution parameters from.

Random randomSource

The random number generator which is used to draw random samples. Optional, can be null.

Return
LogNormal

A log-normal distribution.

double InvCDF(double mu, double sigma, double p)

Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. This is also known as the quantile or percent point function.
MATLAB: logninv
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

double p

The location at which to compute the inverse cumulative density.

Return
double

the inverse cumulative density at p.

bool IsValidParameterSet(double mu, double sigma)

Tests whether the provided values are valid parameters for this distribution.
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

double PDF(double mu, double sigma, double x)

Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
MATLAB: lognpdf
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

double x

The location at which to compute the density.

Return
double

the density at x.

double PDFLn(double mu, double sigma, double x)

Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

double x

The location at which to compute the density.

Return
double

the log density at x.

double Sample(Random rnd, double mu, double sigma)

Generates a sample from the log-normal distribution using the algorithm.
Parameters
Random rnd

The random number generator to use.

double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Return
double

a sample from the distribution.

double Sample(double mu, double sigma)

Generates a sample from the log-normal distribution using the algorithm.
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Return
double

a sample from the distribution.

IEnumerable<double> Samples(Random rnd, double mu, double sigma)

Generates a sequence of samples from the log-normal distribution using the algorithm.
Parameters
Random rnd

The random number generator to use.

double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Return
IEnumerable<double>

a sequence of samples from the distribution.

void Samples(Random rnd, Double[] values, double mu, double sigma)

Fills an array with samples generated from the distribution.
Parameters
Random rnd

The random number generator to use.

Double[] values

The array to fill with the samples.

double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Return
void

a sequence of samples from the distribution.

IEnumerable<double> Samples(double mu, double sigma)

Generates a sequence of samples from the log-normal distribution using the algorithm.
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Return
IEnumerable<double>

a sequence of samples from the distribution.

void Samples(Double[] values, double mu, double sigma)

Fills an array with samples generated from the distribution.
Parameters
Double[] values

The array to fill with the samples.

double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Return
void

a sequence of samples from the distribution.

LogNormal WithMeanVariance(double mean, double var, Random randomSource)

Constructs a log-normal distribution with the desired mean and variance.
Parameters
double mean

The mean of the log-normal distribution.

double var

The variance of the log-normal distribution.

Random randomSource

The random number generator which is used to draw random samples. Optional, can be null.

Return
LogNormal

A log-normal distribution.

LogNormal WithMuSigma(double mu, double sigma, Random randomSource)

Constructs a log-normal distribution with the desired mu and sigma parameters.
Parameters
double mu

The log-scale (μ) of the distribution.

double sigma

The shape (σ) of the distribution. Range: σ ≥ 0.

Random randomSource

The random number generator which is used to draw random samples. Optional, can be null.

Return
LogNormal

A log-normal distribution.

Public Methods

double CumulativeDistribution(double x)

Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
Parameters
double x

The location at which to compute the cumulative distribution function.

Return
double

the cumulative distribution at location x.

double Density(double x)

Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
Parameters
double x

The location at which to compute the density.

Return
double

the density at x.

double DensityLn(double x)

Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
Parameters
double x

The location at which to compute the log density.

Return
double

the log density at x.

bool Equals(object obj)

int GetHashCode()

Type GetType()

double InverseCumulativeDistribution(double p)

Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. This is also known as the quantile or percent point function.
Parameters
double p

The location at which to compute the inverse cumulative density.

Return
double

the inverse cumulative density at p.

double Sample()

Generates a sample from the log-normal distribution using the algorithm.
Return
double

a sample from the distribution.

void Samples(Double[] values)

Fills an array with samples generated from the distribution.

IEnumerable<double> Samples()

Generates a sequence of samples from the log-normal distribution using the algorithm.
Return
IEnumerable<double>

a sequence of samples from the distribution.

string ToString()

A string representation of the distribution.
Return
string

a string representation of the distribution.

Public Properties

double Entropy get;

Gets the entropy of the log-normal distribution.

double Maximum get;

Gets the maximum of the log-normal distribution.

double Mean get;

Gets the mu of the log-normal distribution.

double Median get;

Gets the median of the log-normal distribution.

double Minimum get;

Gets the minimum of the log-normal distribution.

double Mode get;

Gets the mode of the log-normal distribution.

double Mu get;

Gets the log-scale (μ) (mean of the logarithm) of the distribution.

Random RandomSource get; set;

Gets or sets the random number generator which is used to draw random samples.

double Sigma get;

Gets the shape (σ) (standard deviation of the logarithm) of the distribution. Range: σ ≥ 0.

double Skewness get;

Gets the skewness of the log-normal distribution.

double StdDev get;

Gets the standard deviation of the log-normal distribution.

double Variance get;

Gets the variance of the log-normal distribution.