Catalano.Statistics.Distributions

Interface IDiscreteDistribution

All Known Implementing Classes:

BernoulliDistribution, BinomialDistribution, DiscreteUniformDistribution

public interface IDiscreteDistribution

Common interface for discrete distributions.

Method Summary

Modifier and Type	Method and Description
double	DistributionFunction(int k) Gets the cumulative distribution function (cdf) for this distribution evaluated at point k.
double	Entropy() Gets the entropy for this distribution.
double	LogProbabilityMassFunction(int k) Gets the log-probability mass function (pmf) for this distribution evaluated at point x.
double	Mean() Gets the mean for this distribution.
double	ProbabilityMassFunction(int k) Gets the probability mass function (pmf) for this distribution evaluated at point x.
double	Variance() Gets the variance for this distribution.

Method Detail

Mean

double Mean()

Gets the mean for this distribution.

Returns:

Mean.

Variance

double Variance()

Gets the variance for this distribution.

Returns:

Variance.

Entropy

double Entropy()

Gets the entropy for this distribution.

Returns:

Entropy.

DistributionFunction

double DistributionFunction(int k)

Gets 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.

Parameters:

k - A single point in the distribution range.

Returns:

Result.

ProbabilityMassFunction

double ProbabilityMassFunction(int k)

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 k will occur.

Parameters:

k - A single point in the distribution range.

Returns:

The probability of k occurring in the current distribution.

LogProbabilityMassFunction

double LogProbabilityMassFunction(int k)

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.

Parameters:

k - A single point in the distribution range.

Returns:

The logarithm of the probability of k occurring in the current distribution.