Package jsl.utilities.distributions

Class Weibull

java.lang.Object

jsl.utilities.distributions.Distribution

jsl.utilities.distributions.Weibull

All Implemented Interfaces:

ControllableIfc, CDFIfc, ContinuousDistributionIfc, DistributionFunctionIfc, DistributionIfc, DomainIfc, InverseCDFIfc, MeanIfc, PDFIfc, VarianceIfc, GetNameIfc, IdentityIfc, NewInstanceIfc, ParametersIfc, GetRVariableIfc

public class Weibull
extends Distribution
implements ContinuousDistributionIfc, InverseCDFIfc, GetRVariableIfc

This class defines a Weibull distribution

Nested Class Summary

Nested classes/interfaces inherited from class jsl.utilities.distributions.Distribution

Distribution.RandomControls

Field Summary

Fields inherited from class jsl.utilities.distributions.Distribution

myId, myName

Constructor Summary

Constructors

Constructor	Description
Weibull()	Creates new weibull with shape 1.0, scale 1.0
Weibull(double[] parameters)	Constructs a weibull distribution with shape = parameters[0] and scale = parameters[1]
Weibull(double shape, double scale)	Constructs a weibull distribution with supplied shape and scale
Weibull(double shape, double scale, java.lang.String name)	Constructs a weibull distribution with supplied shape and scale

Method Summary

Modifier and Type	Method	Description
double	cdf(double x)	Returns the F(x) = Pr{X <= x} where F represents the cumulative distribution function
Interval	getDomain()
double	getMean()	Returns the mean or expected value of a distribution
double	getMoment3()
double	getMoment4()
double[]	getParameters()	Gets the parameters for the distribution
RVariableIfc	getRandomVariable(RNStreamIfc rng)
double	getScale()	Gets the scale parameter
double	getShape()	Gets the shape
double	getVariance()	Returns the variance of the distribution if defined
double	invCDF(double p)	Provides the inverse cumulative distribution function for the distribution While closed form solutions for the inverse cdf may not exist, numerical search methods can be used to solve F(X) = U.
double	kurtosis()	Gets the kurtosis of the distribution www.mathworld.wolfram.com/WeibullDistribution.html
Weibull	newInstance()	Returns a new instance
double	pdf(double x)	Returns the f(x) where f represents the probability density function for the distribution.
void	setParameters(double[] parameters)	Sets the parameters for the distribution with shape = parameters[0] and scale = parameters[1]
void	setParameters(double shape, double scale)	Sets the parameters
void	setScale(double scale)	Sets the scale parameter
void	setShape(double shape)	Sets the shape parameter
double	skewness()	Gets the skewness of the distribution www.mathworld.wolfram.com/WeibullDistribution.html

Methods inherited from class jsl.utilities.distributions.Distribution

getControls, getId, getName, getStandardDeviation, inverseContinuousCDFViaBisection, inverseContinuousCDFViaBisection, inverseDiscreteCDFViaSearchUp, setControls, setId, setName, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface jsl.utilities.distributions.CDFIfc

cdf, complementaryCDF

Methods inherited from interface jsl.utilities.random.rvariable.GetRVariableIfc

getRandomVariable, getRandomVariable

Constructor Detail

Weibull

public Weibull()

Creates new weibull with shape 1.0, scale 1.0

Weibull

public Weibull(double[] parameters)

Constructs a weibull distribution with shape = parameters[0] and scale = parameters[1]

Parameters:

parameters - An array with the shape and scale

Weibull

public Weibull(double shape,
               double scale)

Constructs a weibull distribution with supplied shape and scale

Parameters:

shape - The shape parameter of the distribution

scale - The scale parameter of the distribution

Weibull

public Weibull(double shape,
               double scale,
               java.lang.String name)

Constructs a weibull distribution with supplied shape and scale

Parameters:

shape - The shape parameter of the distribution

scale - The scale parameter of the distribution

name - an optional name/label

Method Detail

newInstance

public final Weibull newInstance()

Description copied from interface: NewInstanceIfc

Returns a new instance

Specified by:

newInstance in interface NewInstanceIfc

Specified by:

newInstance in class Distribution

Returns:

the new instance

getDomain

public final Interval getDomain()

Specified by:

getDomain in interface DomainIfc

setParameters

public final void setParameters(double shape,
                                double scale)

Sets the parameters

Parameters:

shape - The shape parameter must > 0.0

scale - The scale parameter must be > 0.0

setParameters

public final void setParameters(double[] parameters)

Sets the parameters for the distribution with shape = parameters[0] and scale = parameters[1]

Specified by:

setParameters in interface ParametersIfc

Parameters:

parameters - an array of doubles representing the parameters for the distribution

getParameters

public final double[] getParameters()

Gets the parameters for the distribution

Specified by:

getParameters in interface ParametersIfc

Returns:

Returns an array of the parameters for the distribution

setShape

public final void setShape(double shape)

Sets the shape parameter

Parameters:

shape - The shape parameter must > 0.0

setScale

public final void setScale(double scale)

Sets the scale parameter

Parameters:

scale - The scale parameter must be > 0.0

getShape

public final double getShape()

Gets the shape

Returns:

The shape parameter as a double

getScale

public final double getScale()

Gets the scale parameter

Returns:

The scale parameter as a double

getMean

public final double getMean()

Description copied from interface: MeanIfc

Returns the mean or expected value of a distribution

Specified by:

getMean in interface MeanIfc

Returns:

double the mean or expected value for the distribution

getVariance

public final double getVariance()

Description copied from interface: VarianceIfc

Returns the variance of the distribution if defined

Specified by:

getVariance in interface VarianceIfc

Returns:

double the variance of the random variable

cdf

public final double cdf(double x)

Description copied from interface: CDFIfc

Returns the F(x) = Pr{X <= x} where F represents the cumulative distribution function

Specified by:

cdf in interface CDFIfc

Parameters:

x - a double representing the upper limit

Returns:

a double representing the probability

pdf

public final double pdf(double x)

Description copied from interface: PDFIfc

Returns the f(x) where f represents the probability density function for the distribution. Note this is not a probability.

Specified by:

pdf in interface PDFIfc

Parameters:

x - a double representing the value to be evaluated

Returns:

f(x)

invCDF

public final double invCDF(double p)

Description copied from interface: InverseCDFIfc

Provides the inverse cumulative distribution function for the distribution While closed form solutions for the inverse cdf may not exist, numerical search methods can be used to solve F(X) = U.

Specified by:

invCDF in interface InverseCDFIfc

Parameters:

p - The probability to be evaluated for the inverse, p must be [0,1] or an IllegalArgumentException is thrown

Returns:

The inverse cdf evaluated at the supplied probability

getMoment3

public final double getMoment3()

Returns:

the 3rd moment

getMoment4

public final double getMoment4()

Returns:

the 4th moment

kurtosis

public final double kurtosis()

Gets the kurtosis of the distribution www.mathworld.wolfram.com/WeibullDistribution.html

Returns:

the kurtosis

skewness

public final double skewness()

Gets the skewness of the distribution www.mathworld.wolfram.com/WeibullDistribution.html

Returns:

the skewness

getRandomVariable

public final RVariableIfc getRandomVariable(RNStreamIfc rng)

Specified by:

getRandomVariable in interface GetRVariableIfc

Overrides:

getRandomVariable in class Distribution

Parameters:

rng - the stream to use

Returns:

a random variable