smile.stat.distribution

Class AbstractDistribution

java.lang.Object

smile.stat.distribution.AbstractDistribution

All Implemented Interfaces:

Distribution

Direct Known Subclasses:

BetaDistribution, ChiSquareDistribution, DiscreteDistribution, ExponentialDistribution, FDistribution, GammaDistribution, GaussianDistribution, LogisticDistribution, LogNormalDistribution, Mixture, TDistribution, WeibullDistribution

public abstract class AbstractDistribution
extends java.lang.Object
implements Distribution

This is the base class of univariate distributions. Both rejection and inverse transform sampling methods are implemented to provide some general approaches to generate random samples based on probability density function or quantile function. Besides, a quantile function is also provided based on bisection searching. Likelihood and log likelihood functions are also implemented here.

Constructor Summary

Constructors

Constructor and Description
AbstractDistribution()

Method Summary

Modifier and Type	Method and Description
double	likelihood(double[] x) The likelihood given a sample set following the distribution.
double	logLikelihood(double[] x) The likelihood given a sample set following the distribution.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface smile.stat.distribution.Distribution

cdf, entropy, logp, mean, npara, p, quantile, rand, sd, var

Constructor Detail

AbstractDistribution

public AbstractDistribution()

Method Detail

likelihood

public double likelihood(double[] x)

The likelihood given a sample set following the distribution.

Specified by:

likelihood in interface Distribution

logLikelihood

public double logLikelihood(double[] x)

The likelihood given a sample set following the distribution.

Specified by:

logLikelihood in interface Distribution