Package jsl.utilities.distributions

Class Triangular

java.lang.Object

jsl.utilities.distributions.Distribution

jsl.utilities.distributions.Triangular

All Implemented Interfaces:

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

public class Triangular
extends Distribution
implements ContinuousDistributionIfc, InverseCDFIfc, GetRVariableIfc

Represents the Triangular distribution with parameters - minimum value, maximum value and most likely value

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
Triangular()	Constructs a Triangular distribution with min = 0.0, mode = 0.0, and max = 1.0
Triangular(double[] parameters)	Constructs a Triangular distribution with min = parameters[0], mode = parameters[1], max = parameters[2]
Triangular(double min, double mode, double max)	Constructs a Triangular distribution with min, mode, and max
Triangular(double min, double mode, double max, java.lang.String name)	Constructs a Triangular distribution with min, mode, and max

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
static boolean	checkParameters(double[] param)	Returns true if the parameters are valid for the distribution min = param[0] mode = param[1] max = param[2]
Interval	getDomain()
double	getKurtosis()	Gets the kurtosis of the distribution mu4/mu2^2, www.mathworld.wolfram.com/Kurtosis.html www.mathworld.wolfram.com/TriangularDistribution.html
double	getMaximum()
double	getMean()	Returns the mean or expected value of a distribution
double	getMinimum()
double	getMode()
double	getMoment3()
double	getMoment4()
double[]	getParameters()	Gets the parameters for the distribution
RVariableIfc	getRandomVariable(RNStreamIfc rng)
double	getSkewness()	Gets the skewness of the distribution mu3/mu2^(3/2), www.mathworld.wolfram.com/Skewness.html www.mathworld.wolfram.com/TriangularDistribution.html
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.
Triangular	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 parameters[0] min The minimum value of the distribution parameters[1] mode The mode of the distribution parameters[2] max The maximum value of the distribution
void	setParameters(double min, double mode, double max)	Sets the minimum, most likely and maximum value of the triangular distribution to the private data members myMin, myMode and myMax resp throws IllegalArgumentException when the min >mode, min >= max, mode > max

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

Triangular

public Triangular()

Constructs a Triangular distribution with min = 0.0, mode = 0.0, and max = 1.0

Triangular

public Triangular(double[] parameters)

Constructs a Triangular distribution with min = parameters[0], mode = parameters[1], max = parameters[2]

Parameters:

parameters - The array of parameters

Triangular

public Triangular(double min,
                  double mode,
                  double max)

Constructs a Triangular distribution with min, mode, and max

Parameters:

min - The minimum value of the distribution

mode - The mode of the distribution

max - The maximum value of the distribution

Triangular

public Triangular(double min,
                  double mode,
                  double max,
                  java.lang.String name)

Constructs a Triangular distribution with min, mode, and max

Parameters:

min - The minimum value of the distribution

mode - The mode of the distribution

max - The maximum value of the distribution

name - an optional label/name

Method Detail

newInstance

public final Triangular 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 min,
                                double mode,
                                double max)

Sets the minimum, most likely and maximum value of the triangular distribution to the private data members myMin, myMode and myMax resp throws IllegalArgumentException when the min >mode, min >= max, mode > max

Parameters:

min - The minimum value of the distribution

mode - The mode of the distribution

max - The maximum value of the distribution

checkParameters

public static boolean checkParameters(double[] param)

Returns true if the parameters are valid for the distribution min = param[0] mode = param[1] max = param[2]

Parameters:

param - the parameter array

Returns:

true if the parameters are valid

getMinimum

public final double getMinimum()

Returns:

the minimum of the distribution

getMode

public final double getMode()

Returns:

the mode of the distribution

getMaximum

public final double getMaximum()

Returns:

the maximum of the distribution

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

getMoment3

public final double getMoment3()

Returns:

the 3rd moment

getMoment4

public final double getMoment4()

Returns:

the 4th moment

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

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)

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

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

getKurtosis

public final double getKurtosis()

Gets the kurtosis of the distribution mu4/mu2^2, www.mathworld.wolfram.com/Kurtosis.html www.mathworld.wolfram.com/TriangularDistribution.html

Returns:

the kurtosis

getSkewness

public final double getSkewness()

Gets the skewness of the distribution mu3/mu2^(3/2), www.mathworld.wolfram.com/Skewness.html www.mathworld.wolfram.com/TriangularDistribution.html

Returns:

the skewness

setParameters

public void setParameters(double[] parameters)

Sets the parameters for the distribution parameters[0] min The minimum value of the distribution parameters[1] mode The mode of the distribution parameters[2] max The maximum value of the distribution

Specified by:

setParameters in interface ParametersIfc

Parameters:

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

getParameters

public double[] getParameters()

Gets the parameters for the distribution

Specified by:

getParameters in interface ParametersIfc

Returns:

Returns an array of the parameters for the distribution

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