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

Inheritance: UnivariateDiscreteDistribution
显示文件 Open project: accord-net/framework Class Usage Examples

Public Methods

Method Description
Clone ( ) : object

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

DistributionFunction ( int k ) : double

Gets P( X<= k), the cumulative distribution function (cdf) for this distribution evaluated at point k.

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.

LogProbabilityMassFunction ( int k ) : 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 k will occur.

NegativeBinomialDistribution ( [ failures, [ probability ) : System

Creates a new Negative Binomial distribution.

ProbabilityMassFunction ( int k ) : 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 method

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

DistributionFunction() public method

Gets P( X<= k), the cumulative distribution function (cdf) for this distribution evaluated at point k.
The Cumulative Distribution Function (CDF) describes the cumulative probability that a given value or any value smaller than it will occur.
public DistributionFunction ( int k ) : double
k int A single point in the distribution range.
return double

Fit() public method

Fits the underlying distribution to a given set of observations.
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.
return void

LogProbabilityMassFunction() public method

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 k will occur.
public LogProbabilityMassFunction ( int k ) : double
k int A single point in the distribution range.
return double

NegativeBinomialDistribution() public method

Creates a new Negative Binomial distribution.
public NegativeBinomialDistribution ( [ failures, [ probability ) : System
failures [ Number of failures r.
probability [ Success probability in each experiment.
return System

ProbabilityMassFunction() public method

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 k ) : double
k int A single point in the distribution range.
return double

ToString() public method

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