C# Class Accord.Statistics.Distributions.Univariate.NormalDistribution

Inheritance: UnivariateContinuousDistribution

Méthodes publiques

Méthode	Description
Clone ( ) : object	Creates a new object that is a copy of the current instance.
DistributionFunction ( double x ) : double	Gets the cumulative distribution function (cdf) for the this distribution evaluated at point `x`. The Cumulative Distribution Function (CDF) describes the cumulative probability that a given value or any value smaller than it will occur. The calculation is computed through the relationship to the function as erfc(-z/sqrt(2)) / 2. References: http://mathworld.wolfram.com/NormalDistributionFunction.html
Fit ( double observations, double weights ) : IDistribution	Fits the underlying distribution to a given set of observations.
NormalDistribution ( ) : System	Constructs a Gaussian distribution with zero mean and unit variance.
NormalDistribution ( double mean ) : System	Constructs a Gaussian distribution with given mean and unit variance.
NormalDistribution ( double mean, double variance ) : System	Constructs a Gaussian distribution with given mean and given variance.
ProbabilityDensityFunction ( double x ) : double	Gets the probability density function (pdf) for the Gaussian distribution evaluated at point `x`. The Probability Density Function (PDF) describes the probability that a given value `x` will occur.
ZScore ( double x ) : double	Gets the Z-Score for a given value.

Creates a new object that is a copy of the current instance.

public Clone ( ) : object
Résultat	object

Gets the cumulative distribution function (cdf) for the this distribution evaluated at point x.

The Cumulative Distribution Function (CDF) describes the cumulative probability that a given value or any value smaller than it will occur.

The calculation is computed through the relationship to the function as erfc(-z/sqrt(2)) / 2.

public DistributionFunction ( double x ) : double
x	double	/// A single point in the distribution range.
Résultat	double

Fits the underlying distribution to a given set of observations.

public Fit ( double observations, double weights ) : IDistribution
observations	double	/// The array of observations to fit the model against. ///
weights	double	/// The weight vector containing the weight for each of the samples. ///
Résultat	IDistribution

Constructs a Gaussian distribution with zero mean and unit variance.

public NormalDistribution ( ) : System
Résultat	System

Constructs a Gaussian distribution with given mean and unit variance.

public NormalDistribution ( double mean ) : System
mean	double
Résultat	System

Constructs a Gaussian distribution with given mean and given variance.

public NormalDistribution ( double mean, double variance ) : System
mean	double
variance	double
Résultat	System

Gets the probability density function (pdf) for the Gaussian distribution evaluated at point x.

The Probability Density Function (PDF) describes the probability that a given value x will occur.

public ProbabilityDensityFunction ( double x ) : double
x	double	A single point in the distribution range. For a /// univariate distribution, this should be a single /// double value. For a multivariate distribution, /// this should be a double array.
Résultat	double

Gets the Z-Score for a given value.

public ZScore ( double x ) : double
x	double
Résultat	double