C# Class Accord.Statistics.Distributions.Multivariate.HiddenMarkovDistribution

Hidden Markov Model probability distribution.
Inheritance: MultivariateDiscreteDistribution
Afficher le fichier Open project: accord-net/framework

Méthodes publiques

Méthode Description
Clone ( ) : object

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

DistributionFunction ( int x ) : double

Gets the cumulative distribution function (cdf) for 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.

Fit ( double observations, double weights, Fitting options ) : void

Fits the underlying distribution to a given set of observations.

Although both double[] and double[][] arrays are supported, providing a double[] for a multivariate distribution or a double[][] for a univariate distribution may have a negative impact in performance.

Fit ( double observations, double weights, HiddenMarkovOptions options ) : void

Fits the underlying distribution to a given set of observations.

Although both double[] and double[][] arrays are supported, providing a double[] for a multivariate distribution or a double[][] for a univariate distribution may have a negative impact in performance.

HiddenMarkovDistribution ( HiddenMarkovModel model ) : System

Initializes a new instance of the HiddenMarkovDistribution class.

LogProbabilityMassFunction ( int x ) : double

Gets the log-probability mass function (pmf) for this distribution evaluated at point x.

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

ProbabilityMassFunction ( int x ) : double

Gets the probability mass function (pmf) for this distribution evaluated at point x.

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

ToString ( string format, IFormatProvider formatProvider ) : string

Returns a System.String that represents this instance.

Method Details

Clone() public méthode

Creates a new object that is a copy of the current instance.
public Clone ( ) : object
Résultat object

DistributionFunction() public méthode

Gets the cumulative distribution function (cdf) for 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.
public DistributionFunction ( int x ) : double
x int A single point in the distribution range.
Résultat double

Fit() public méthode

Fits the underlying distribution to a given set of observations.
Although both double[] and double[][] arrays are supported, providing a double[] for a multivariate distribution or a double[][] for a univariate distribution may have a negative impact in performance.
public Fit ( double observations, double weights, Fitting options ) : void
observations double The array of observations to fit the model against. The array /// elements can be either of type double (for univariate data) or /// type double[] (for multivariate data).
weights double The weight vector containing the weight for each of the samples.
options Fitting Optional arguments which may be used during fitting, such /// as regularization constants and additional parameters.
Résultat void

Fit() public méthode

Fits the underlying distribution to a given set of observations.
Although both double[] and double[][] arrays are supported, providing a double[] for a multivariate distribution or a double[][] for a univariate distribution may have a negative impact in performance.
public Fit ( double observations, double weights, HiddenMarkovOptions options ) : void
observations double The array of observations to fit the model against. The array /// elements can be either of type double (for univariate data) or /// type double[] (for multivariate data).
weights double The weight vector containing the weight for each of the samples.
options Accord.Statistics.Distributions.Fitting.HiddenMarkovOptions Optional arguments which may be used during fitting, such /// as regularization constants and additional parameters.
Résultat void

HiddenMarkovDistribution() public méthode

Initializes a new instance of the HiddenMarkovDistribution class.
public HiddenMarkovDistribution ( HiddenMarkovModel model ) : System
model Accord.Statistics.Models.Markov.HiddenMarkovModel The model.
Résultat System

LogProbabilityMassFunction() public méthode

Gets the log-probability mass function (pmf) for this distribution evaluated at point x.
The Probability Mass Function (PMF) describes the probability that a given value x will occur.
public LogProbabilityMassFunction ( int x ) : double
x int A single point in the distribution range.
Résultat double

ProbabilityMassFunction() public méthode

Gets the probability mass function (pmf) for this distribution evaluated at point x.
The Probability Mass Function (PMF) describes the probability that a given value x will occur.
public ProbabilityMassFunction ( int x ) : double
x int A single point in the distribution range.
Résultat double

ToString() public méthode

Returns a System.String that represents this instance.
public ToString ( string format, IFormatProvider formatProvider ) : string
format string The format.
formatProvider IFormatProvider The format provider.
Résultat string