com.imsl.stat.distributions

Class ProbabilityDistribution

java.lang.Object

com.imsl.stat.distributions.ProbabilityDistribution

All Implemented Interfaces:

Serializable, Cloneable

Direct Known Subclasses:

BetaPD, ContinuousUniformPD, ExponentialPD, ExtremeValuePD, GammaPD, GeneralizedGaussianPD, GeometricPD, LogisticPD, LogNormalPD, NormalPD, ParetoPD, PoissonPD, RayleighPD, WeibullPD

public abstract class ProbabilityDistribution
extends Object
implements Serializable, Cloneable

The ProbabilityDistribution abstract class defines members and methods common to univariate probability distributions and useful in parameter estimation.

See Also:

Serialized Form

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	ProbabilityDistribution(int numberOfParameters) Constructor for the probability distribution

Method Summary

Modifier and Type	Method and Description
int	getNumberOfParameters() Returns the number of parameters of the probability distribution.
abstract double[]	getParameterLowerBounds() Returns the lower bounds of the parameters.
abstract double[]	getParameterUpperBounds() Returns the upper bounds of the parameters.
double[]	getPDFGradientApproximation(double x, double... params) Returns the approximate gradient of the probability density function, pdf.
double[][]	getPDFHessianApproximation(double x, double... params) Returns the approximate hessian of the probability density function, pdf.
double[]	getRangeOfX() Returns the proper range of the random variable having the current probability distribution.
abstract double	pdf(double x, double... params) Returns the value of the probability density function.
void	setRangeOfX(double[] range) Sets the proper range of the random variable having the current probability distribution.

Methods inherited from class java.lang.Object

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

Constructor Detail

ProbabilityDistribution

protected ProbabilityDistribution(int numberOfParameters)

Constructor for the probability distribution

Parameters:

numberOfParameters - an int specifying the number of parameters

Every subclass (specific probability distribution) must set the number of parameters.

Method Detail

getNumberOfParameters

public int getNumberOfParameters()

Returns the number of parameters of the probability distribution.

Returns:

an int, the number of parameters

getRangeOfX

public double[] getRangeOfX()

Returns the proper range of the random variable having the current probability distribution.

Returns:

a double array containing the lower bound (at index 0) and upper bound (at index 1) for the random variable X

setRangeOfX

public void setRangeOfX(double[] range)

Sets the proper range of the random variable having the current probability distribution.

Parameters:

range - a double array containing the lower bound (at index 0) and the upper bound (at index 1) for the random variable

Default: range[0]=Double.NEGATIVE_INFINITY and range[1]=Double.POSITIVE_INFINITY.

getParameterLowerBounds

public abstract double[] getParameterLowerBounds()

Returns the lower bounds of the parameters.

Each ProbabilityDistribution subclass must override this method.

Returns:

a double array containing the lower bounds of the parameters

getParameterUpperBounds

public abstract double[] getParameterUpperBounds()

Returns the upper bounds of the parameters.

Each ProbabilityDistribution subclass must override this method.

Returns:

a double array containing the upper bounds of the parameters

pdf

public abstract double pdf(double x,
                           double... params)

Returns the value of the probability density function.

Each ProbabilityDistribution subclass must override this method.

Parameters:

x - a double value

params - a double array or a comma-separated list of doubles giving the values for the parameters

Note: The argument params is a variable length argument list (varargs).

Returns:

a double value equal to the probability density function given the parameters evaluated at X=x

getPDFGradientApproximation

public double[] getPDFGradientApproximation(double x,
                                            double... params)

Returns the approximate gradient of the probability density function, pdf.

Parameters:

x - a double value

params - a double array or a comma-separated list of doubles giving the values for the parameters

Note: The argument params is a variable length argument list (varargs).

Returns:

a double array containing the gradient approximation given the parameter values and evaluated at X=x

getPDFHessianApproximation

public double[][] getPDFHessianApproximation(double x,
                                             double... params)

Returns the approximate hessian of the probability density function, pdf.

Parameters:

x - a double value

params - a double array or a comma-separated list of doubles giving the values for the parameters

Note: The argument params is a variable length argument list (varargs).

Returns:

a double matrix equal to the second partial derivatives of the probability density function with respect to the parameters evaluated at X=x