jsat.distributions.discrete

Class Zipf

java.lang.Object

jsat.distributions.Distribution

jsat.distributions.discrete.DiscreteDistribution

jsat.distributions.discrete.Zipf

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable

public class Zipf
extends DiscreteDistribution

This class provides an implementation of the Zipf distribution, a power-law type distribution for discrete values.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Zipf() Creates a new Zipf distribution of infinite cardinality and skewness of 1.
Zipf(double skew) Creates a new Zipf distribution for a set of infinite cardinality
Zipf(double cardinality, double skew) Creates a new Zipf distribution
Zipf(Zipf toCopy) Copy constructor

Method Summary

Modifier and Type	Method and Description
double	cdf(int x) Computes the value of the Cumulative Density Function (CDF) at the given point.
Zipf	clone()
double	getCardinality()
double	getSkew()
double	invCdf(double p) Computes the inverse Cumulative Density Function (CDF-1) at the given point.
double	max() The maximum value for which the #pdf(double) is meant to return a value.
double	mean() Computes the mean value of the distribution
double	min() The minimum value for which the #pdf(double) is meant to return a value.
double	mode() Computes the mode of the distribution.
double	pmf(int x)
void	setCardinality(double cardinality) Sets the cardinality of the distribution, defining the maximum number of items that Zipf can return.
void	setSkew(double skew) Sets the skewness of the distribution.
double	skewness() Computes the skewness of the distribution.
double	variance() Computes the variance of the distribution.

Methods inherited from class jsat.distributions.discrete.DiscreteDistribution

cdf, logPmf

Methods inherited from class jsat.distributions.Distribution

median, sample, sampleVec, standardDeviation

Methods inherited from class java.lang.Object

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

Constructor Detail

Zipf

public Zipf(double cardinality,
            double skew)

Creates a new Zipf distribution

Parameters:

cardinality - the number of possible selections (or Double.POSITIVE_INFINITY)

skew - the skewness of the distribution (must be positive value)

Zipf

public Zipf(double skew)

Creates a new Zipf distribution for a set of infinite cardinality

Parameters:

skew - the skewness of the distribution (must be positive value)

Zipf

public Zipf()

Creates a new Zipf distribution of infinite cardinality and skewness of 1.

Zipf

public Zipf(Zipf toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

Method Detail

setCardinality

public void setCardinality(double cardinality)

Sets the cardinality of the distribution, defining the maximum number of items that Zipf can return.

Parameters:

cardinality - the maximum output range of the distribution, can be infinite.

getCardinality

public double getCardinality()

Returns:

the cardinality (maximum value) of the distribution

setSkew

public void setSkew(double skew)

Sets the skewness of the distribution. Lower values spread out the probability distribution, while higher values concentrate on the lowest ranks.

Parameters:

skew - the positive value for the distribution's skew

getSkew

public double getSkew()

Returns:

the skewness of the distribution

pmf

public double pmf(int x)

Specified by:

pmf in class DiscreteDistribution

cdf

public double cdf(int x)

Description copied from class: DiscreteDistribution

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.

Specified by:

cdf in class DiscreteDistribution

Parameters:

x - the value to get the CDF of

Returns:

the CDF(x)

invCdf

public double invCdf(double p)

Description copied from class: Distribution

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

Overrides:

invCdf in class DiscreteDistribution

Parameters:

p - the probability value

Returns:

the value such that the CDF would return p

clone

public Zipf clone()

Specified by:

clone in class DiscreteDistribution

mean

public double mean()

Description copied from class: Distribution

Computes the mean value of the distribution

Specified by:

mean in class Distribution

Returns:

the mean value of the distribution

mode

public double mode()

Description copied from class: Distribution

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.

Specified by:

mode in class Distribution

Returns:

the mode of the distribution

variance

public double variance()

Description copied from class: Distribution

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.

Specified by:

variance in class Distribution

Returns:

the variance of the distribution.

skewness

public double skewness()

Description copied from class: Distribution

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.

Specified by:

skewness in class Distribution

Returns:

the skewness of the distribution.

min

public double min()

Description copied from class: Distribution

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

Specified by:

min in class Distribution

Returns:

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

max

public double max()

Description copied from class: Distribution

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

Specified by:

max in class Distribution

Returns:

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