Package jsl.utilities.distributions

Class ShiftedGeometric

java.lang.Object

jsl.utilities.distributions.Distribution

jsl.utilities.distributions.ShiftedGeometric

All Implemented Interfaces:

ControllableIfc, CDFIfc, DiscreteDistributionIfc, DistributionFunctionIfc, DistributionIfc, InverseCDFIfc, MeanIfc, PMFIfc, VarianceIfc, GetNameIfc, IdentityIfc, NewInstanceIfc, ParametersIfc, GetRVariableIfc

public class ShiftedGeometric
extends Distribution
implements DiscreteDistributionIfc, GetRVariableIfc

The ShiftedeGeometric distribution is the probability distribution of the number of Bernoulli trials needed to get one success. supported on the set {1, 2, 3, ... }

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
ShiftedGeometric()	Constructs a ShiftedGeometric with success probability = 0.5
ShiftedGeometric(double prob)	Constructs a ShiftedGeometric using the supplied success probability
ShiftedGeometric(double[] parameters)	Constructs a ShiftedGeometric using the supplied parameters array parameters[0] is probability of success
ShiftedGeometric(double prob, java.lang.String name)	Constructs a ShiftedGeometric using the supplied success probability

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
double	getMean()	Returns the mean or expected value of a distribution
double[]	getParameters()	Gets the parameters as an array parameters[0] is probability of success
double	getProbabilityOfSuccess()	Gets the probability of success
RVariableIfc	getRandomVariable(RNStreamIfc rng)
double	getVariance()	Returns the variance of the distribution if defined
double	invCDF(double prob)	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.
ShiftedGeometric	newInstance()	Returns a new instance
double	pmf(double x)	Returns the f(x) where f represents the probability mass function for the distribution.
double	pmf(int x)	computes the pmf of the distribution f(x) = p(1-p)^(x-1.0)
void	setParameters(double[] parameters)	Sets the parameters using the supplied array parameters[0] is probability of success
void	setProbabilityOfSuccess(double prob)	Sets the probability of success

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

ShiftedGeometric

public ShiftedGeometric()

Constructs a ShiftedGeometric with success probability = 0.5

ShiftedGeometric

public ShiftedGeometric(double[] parameters)

Constructs a ShiftedGeometric using the supplied parameters array parameters[0] is probability of success

Parameters:

parameters -

ShiftedGeometric

public ShiftedGeometric(double prob)

Constructs a ShiftedGeometric using the supplied success probability

Parameters:

prob - the probability of success

ShiftedGeometric

public ShiftedGeometric(double prob,
                        java.lang.String name)

Constructs a ShiftedGeometric using the supplied success probability

Parameters:

prob - the probability of success

name - an optional name/label

Method Detail

newInstance

public final ShiftedGeometric 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

setProbabilityOfSuccess

public final void setProbabilityOfSuccess(double prob)

Sets the probability of success

Parameters:

prob - the probability of success

getProbabilityOfSuccess

public final double getProbabilityOfSuccess()

Gets the probability of success

Returns:

the probability of success

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

setParameters

public final void setParameters(double[] parameters)

Sets the parameters using the supplied array parameters[0] is probability of success

Specified by:

setParameters in interface ParametersIfc

Parameters:

parameters - the parameter array

getParameters

public final double[] getParameters()

Gets the parameters as an array parameters[0] is probability of success

Specified by:

getParameters in interface ParametersIfc

Returns:

the parameter array

pmf

public final double pmf(int x)

computes the pmf of the distribution f(x) = p(1-p)^(x-1.0)

Parameters:

x - the value to evaluate

Returns:

the probability at x

pmf

public final double pmf(double x)

Description copied from interface: PMFIfc

Returns the f(x) where f represents the probability mass function for the distribution.

Specified by:

pmf in interface PMFIfc

Parameters:

x - a double representing the value to be evaluated

Returns:

f(x) the P(X=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 prob)

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:

prob - 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

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