org.ojalgo.random

Interface ContinuousDistribution

All Superinterfaces:

Distribution

All Known Implementing Classes:

Exponential, LogNormal, Normal, Uniform

public interface ContinuousDistribution
extends Distribution

Method Summary

Modifier and Type	Method and Description
double	getDistribution(double value) In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x.
double	getProbability(double value) In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point.
double	getQuantile(double probality) The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function.

Methods inherited from interface org.ojalgo.random.Distribution

getExpected, getStandardDeviation, getVariance

Method Detail

getDistribution

double getDistribution(double value)

In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x. Intuitively, it is the "area so far" function of the probability distribution. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. WikipediA

Parameters:

value - x

Returns:

P(<=x)

getProbability

double getProbability(double value)

In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. The probability for the random variable to fall within a particular region is given by the integral of this variable's density over the region. The probability density function is nonnegative everywhere, and its integral over the entire space is equal to one. WikipediA

Parameters:

value - x

Returns:

P(x)

getQuantile

double getQuantile(double probality)

The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function. WikipediA The input probability absolutely has to be [0.0, 1.0], but values close to 0.0 and 1.0 may be problematic

Parameters:

probality - P(<=x)

Returns:

x