org.ojalgo.random

## Interface ContinuousDistribution

• ### Method Summary

All Methods
Modifier and Type Method and Description
`double` `getDensity(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` `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.
`default double` `getProbability(double value)`
Deprecated.
`double` `getQuantile(double probability)`
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

• #### getDensity

`double getDensity(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)
• #### 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

```@Deprecated
default double getProbability(double value)```
Deprecated. v48 Use `getDensity(double)` instead
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 probability)`
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:
`probability` - P(<=x)
Returns:
x