jsat.distributions

Class ContinuousDistribution

java.lang.Object

jsat.distributions.Distribution

jsat.distributions.ContinuousDistribution

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

Beta, Cauchy, ChiSquared, Exponential, FisherSendor, Gamma, KernelDensityEstimator, Kolmogorov, Kumaraswamy, Laplace, Levy, Logistic, LogNormal, LogUniform, MaxwellBoltzmann, Normal, Pareto, Rayleigh, StudentT, TruncatedDistribution, Uniform, Weibull

public abstract class ContinuousDistribution
extends Distribution

The ContinuousDistribution represents the contract for a continuous in one dimension.

Many of the functions of a Continuous Distribution are implemented by default using numerical calculation and integration. For this reason, the base implementations may be slower or less accurate than desired - and could produce incorrect results for poorly behaved functions or large magnitude inputs. These base implementations are provided for easy completeness, but may not be appropriate for all methods. If needed, the implementer should check if these methods provide the needed level of accuracy and speed.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ContinuousDistribution()

Method Summary

Modifier and Type	Method and Description
double	cdf(double x) Computes the value of the Cumulative Density Function (CDF) at the given point.
abstract ContinuousDistribution	clone()
abstract double[]	getCurrentVariableValues() Returns an array, where each value contains the value of a parameter in the distribution.
java.lang.String	getDescriptiveName() The descriptive name of a distribution returns the name of the distribution, followed by the parameters of the distribution and their values.
abstract java.lang.String	getDistributionName() Return the name of the distribution.
abstract java.lang.String[]	getVariables() Returns an array, where each value contains the name of a parameter in the distribution.
double	invCdf(double p) Computes the inverse Cumulative Density Function (CDF-1) at the given point.
double	logPdf(double x) Computes the log of the Probability Density Function.
double	mean() Computes the mean value of the distribution
double	mode() Computes the mode of the distribution.
abstract double	pdf(double x) Computes the value of the Probability Density Function (PDF) at the given point
abstract void	setUsingData(Vec data) Attempts to set the variables used by this distribution based on population sample data, assuming the sample data is from this type of distribution.
abstract void	setVariable(java.lang.String var, double value) Sets one of the variables of this distribution by the name.
double	skewness() Computes the skewness of the distribution.
java.lang.String	toString()
double	variance() Computes the variance of the distribution.

Methods inherited from class jsat.distributions.Distribution

max, median, min, sample, sampleVec, standardDeviation

Methods inherited from class java.lang.Object

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

Constructor Detail

ContinuousDistribution

public ContinuousDistribution()

Method Detail

logPdf

public double logPdf(double x)

Computes the log of the Probability Density Function. Note, that then the probability is zero, Double.NEGATIVE_INFINITY would be the true value. Instead, this method will always return the negative of Double.MAX_VALUE. This is to avoid propagating bad values through computation.

Parameters:

x - the value to get the log(PDF) of

Returns:

the value of log(PDF(x))

pdf

public abstract double pdf(double x)

Computes the value of the Probability Density Function (PDF) at the given point

Parameters:

x - the value to get the PDF

Returns:

the PDF(x)

cdf

public double cdf(double x)

Description copied from class: Distribution

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 Distribution

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 Distribution

Parameters:

p - the probability value

Returns:

the value such that the CDF would return p

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

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.

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

getDescriptiveName

public java.lang.String getDescriptiveName()

The descriptive name of a distribution returns the name of the distribution, followed by the parameters of the distribution and their values.

Returns:

the name of the distribution that includes parameter values

getDistributionName

public abstract java.lang.String getDistributionName()

Return the name of the distribution.

Returns:

the name of the distribution.

getVariables

public abstract java.lang.String[] getVariables()

Returns an array, where each value contains the name of a parameter in the distribution. The order must always be the same, and match up with the values returned by getCurrentVariableValues()

Returns:

a string of the variable names this distribution uses

getCurrentVariableValues

public abstract double[] getCurrentVariableValues()

Returns an array, where each value contains the value of a parameter in the distribution. The order must always be the same, and match up with the values returned by getVariables()

Returns:

the current values of the parameters used by this distribution, in the same order as their names are returned by getVariables()

setVariable

public abstract void setVariable(java.lang.String var,
                                 double value)

Sets one of the variables of this distribution by the name.

Parameters:

var - the variable to set

value - the value to set

clone

public abstract ContinuousDistribution clone()

Specified by:

clone in class Distribution

setUsingData

public abstract void setUsingData(Vec data)

Attempts to set the variables used by this distribution based on population sample data, assuming the sample data is from this type of distribution.

Parameters:

data - the data to use to attempt to fit against

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object