com.imsl.stat
Class PoissonDistribution

java.lang.Object
  com.imsl.stat.PoissonDistribution

All Implemented Interfaces:

Distribution, ProbabilityDistribution, Serializable

public class PoissonDistribution
extends Object
implements ProbabilityDistribution, Serializable

Evaluates a Poisson probability density of a given set of data.

The poissonDistribution evaluates the Poisson probability density of a given set of data, xData. If parameters are not supplied, the eval method fits the Poisson probability density function by first calculating theta, . The Poisson probability density function is defined as:

The DataMining package class NaiveBayesClassifier uses PoissonDistribution as a method to train continuous data.

See Also:

Example, Serialized Form

Constructor Summary

PoissonDistribution()

Method Summary

double[]	eval(double[] xData) Fits a Poisson probability distribution to xData and returns the probability density at each value.
double[]	eval(double[] xData, Object[] parameters) Evaluates a Poisson probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
double	eval(double xData, Object[] parameters) Evaluates a Poisson probability density function at a given point xData.
Object[]	getParameters() Returns the current parameters of the Poisson probability density function.
double	getTheta() Returns the mean number of successes in a given time period of the Poisson probability distribution.

Methods inherited from class java.lang.Object

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

Constructor Detail

PoissonDistribution

public PoissonDistribution()

Method Detail

eval

public double[] eval(double[] xData)

Fits a Poisson probability distribution to xData and returns the probability density at each value.

Specified by:

eval in interface Distribution

Parameters:

xData - a double array representing the points at which the Poisson probability distribution function is to be evaluated

Returns:

a double array representing the Poisson probability density at each value of xData

eval

public double[] eval(double[] xData,
                     Object[] parameters)

Evaluates a Poisson probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.

Specified by:

eval in interface ProbabilityDistribution

Parameters:

xData - a double array representing the points at which the Poisson probability distribution function is to be evaluated

parameters - an Object array representing the parameters used to evaluate the Poisson distribution, see method getParameters

Returns:

a double array representing the Poisson probability density at each value of xData

eval

public double eval(double xData,
                   Object[] parameters)

Evaluates a Poisson probability density function at a given point xData.

Specified by:

eval in interface ProbabilityDistribution

Parameters:

xData - a double representing the point at which the Poisson probability distribution function is to be evaluated

parameters - an Object array representing the parameters used to evaluate the Poisson distribution, see method getParameters

Returns:

a double representing the Poisson probability density at xData

getParameters

public Object[] getParameters()

Returns the current parameters of the Poisson probability density function.

Specified by:

getParameters in interface ProbabilityDistribution

Returns:

an Object array containing the parameters resulting from the last invocation of the (Distribution) eval method with the following signature, double[] eval(double[] xData). This Object array can be used as input to the eval methods that require an Object array of distribution parameters as input.

getTheta

public double getTheta()

Returns the mean number of successes in a given time period of the Poisson probability distribution.

Returns:

a double representing the mean number of successes in a given time period of the Poisson probability distribution