Distribution (OpenChemLib 2021.2.0 API)

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

AbstractDistribution, GaussianDistribution, Mixture
```
public interface Distribution
extends java.io.Serializable
```
Probability distribution of univariate random variable. A probability distribution identifies either the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). When the random variable takes values in the set of real numbers, the probability distribution is completely described by the cumulative distribution function, whose value at each real x is the probability that the random variable is smaller than or equal to x.

Author:

Haifeng Li

See Also:

MultivariateDistribution

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`double`	`cdf(double x)`	Cumulative distribution function.
`double`	`entropy()`	Shannon entropy of the distribution.
`double`	`likelihood(double[] x)`	The likelihood of the sample set following this distribution.
`double`	`logLikelihood(double[] x)`	The log likelihood of the sample set following this distribution.
`double`	`logp(double x)`	The density at x in log scale, which may prevents the underflow problem.
`double`	`mean()`	The mean of distribution.
`int`	`npara()`	The number of parameters of the distribution.
`double`	`p(double x)`	The probability density function for continuous distribution or probability mass function for discrete distribution at x.
`double`	`quantile(double p)`	The quantile, the probability to the left of quantile is p.
`double`	`rand()`	Generates a random number following this distribution.
`double`	`sd()`	The standard deviation of distribution.
`double`	`var()`	The variance of distribution.

- Method Detail
  - npara
```
int npara()
```
    The number of parameters of the distribution.
  - mean
```
double mean()
```
    The mean of distribution.
  - var
```
double var()
```
    The variance of distribution.
  - sd
```
double sd()
```
    The standard deviation of distribution.
  - entropy
```
double entropy()
```
    Shannon entropy of the distribution.
  - rand
```
double rand()
```
    Generates a random number following this distribution.
  - p
```
double p(double x)
```
    The probability density function for continuous distribution or probability mass function for discrete distribution at x.
  - logp
```
double logp(double x)
```
    The density at x in log scale, which may prevents the underflow problem.
  - cdf
```
double cdf(double x)
```
    Cumulative distribution function. That is the probability to the left of x.
  - quantile
```
double quantile(double p)
```
    The quantile, the probability to the left of quantile is p. It is actually the inverse of cdf.
  - likelihood
```
double likelihood(double[] x)
```
    The likelihood of the sample set following this distribution.
  - logLikelihood
```
double logLikelihood(double[] x)
```
    The log likelihood of the sample set following this distribution.