jsat.distributions

Class Distribution

java.lang.Object

jsat.distributions.Distribution

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

ContinuousDistribution, DiscreteDistribution

public abstract class Distribution
extends java.lang.Object
implements java.lang.Cloneable, java.io.Serializable

Base distribution class for distributions that have only one input.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Distribution()

Method Summary

Modifier and Type	Method and Description
abstract double	cdf(double x) Computes the value of the Cumulative Density Function (CDF) at the given point.
abstract Distribution	clone()
double	invCdf(double p) Computes the inverse Cumulative Density Function (CDF-1) at the given point.
abstract double	max() The maximum value for which the #pdf(double) is meant to return a value.
abstract double	mean() Computes the mean value of the distribution
double	median() Computes the median value of the distribution
abstract double	min() The minimum value for which the #pdf(double) is meant to return a value.
abstract double	mode() Computes the mode of the distribution.
double[]	sample(int numSamples, java.util.Random rand) This method returns a double array containing the values of random samples from this distribution.
DenseVector	sampleVec(int numSamples, java.util.Random rand) This method returns a double array containing the values of random samples from this distribution.
abstract double	skewness() Computes the skewness of the distribution.
double	standardDeviation() Computes the standard deviation of the distribution.
abstract double	variance() Computes the variance of the distribution.

Methods inherited from class java.lang.Object

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

Constructor Detail

Distribution

public Distribution()

Method Detail

cdf

public abstract double cdf(double x)

Computes the value of the Cumulative Density Function (CDF) at the given point. The CDF returns a value in the range [0, 1], indicating what portion of values occur at or below that point.

Parameters:

x - the value to get the CDF of

Returns:

the CDF(x)

invCdf

public double invCdf(double p)

Computes the inverse Cumulative Density Function (CDF^-1) at the given point. It takes in a value in the range of [0, 1] and returns the value x, such that CDF(x) = p

Parameters:

p - the probability value

Returns:

the value such that the CDF would return p

mean

public abstract double mean()

Computes the mean value of the distribution

Returns:

the mean value of the distribution

median

public double median()

Computes the median value of the distribution

Returns:

the median value of the distribution

mode

public abstract double mode()

Computes the mode of the distribution. Not all distributions have a mode for all parameter values. NaN may be returned if the mode is not defined for the current values of the distribution.

Returns:

the mode of the distribution

variance

public abstract double variance()

Computes the variance of the distribution. Not all distributions have a finite variance for all parameter values. NaN may be returned if the variance is not defined for the current values of the distribution. Infinity is a possible value to be returned by some distributions.

Returns:

the variance of the distribution.

skewness

public abstract double skewness()

Computes the skewness of the distribution. Not all distributions have a finite skewness for all parameter values. NaN may be returned if the skewness is not defined for the current values of the distribution.

Returns:

the skewness of the distribution.

standardDeviation

public double standardDeviation()

Computes the standard deviation of the distribution. Not all distributions have a finite standard deviation for all parameter values. NaN may be returned if the variance is not defined for the current values of the distribution. Infinity is a possible value to be returned by some distributions.

Returns:

the standard deviation of the distribution

min

public abstract double min()

The minimum value for which the #pdf(double) is meant to return a value. Note that Double.NEGATIVE_INFINITY is a valid return value.

Returns:

the minimum value for which the #pdf(double) is meant to return a value.

max

public abstract double max()

The maximum value for which the #pdf(double) is meant to return a value. Note that Double.POSITIVE_INFINITY is a valid return value.

Returns:

the maximum value for which the #pdf(double) is meant to return a value.

sample

public double[] sample(int numSamples,
                       java.util.Random rand)

This method returns a double array containing the values of random samples from this distribution.

Parameters:

numSamples - the number of random samples to take

rand - the source of randomness

Returns:

an array of the random sample values

sampleVec

public DenseVector sampleVec(int numSamples,
                             java.util.Random rand)

This method returns a double array containing the values of random samples from this distribution.

Parameters:

numSamples - the number of random samples to take

rand - the source of randomness

Returns:

a vector of the random sample values

clone

public abstract Distribution clone()

Overrides:

clone in class java.lang.Object