com.itemanalysis.psychometrics.distribution

Class ContinuousDistributionApproximation

java.lang.Object

com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation

com.itemanalysis.psychometrics.distribution.ContinuousDistributionApproximation

All Implemented Interfaces:

DistributionApproximation

public class ContinuousDistributionApproximation
extends AbstractDistributionApproximation

A class that provides a discrete approximation of a univariate continuous probability distribution. Initial values may be from a normal distribution or a uniform distribution. The points and weights may be updated, which may result in something other than a normal or uniform distribution (i.e. an empirical histogram). Methods allow the distribution to be standardized to have a mean of zero and a standard deviaiton of one.

Field Summary

Fields inherited from class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation

max, min, normal, numberOfPoints, points, range, step, weights

Constructor Summary

Constructors

Constructor and Description
ContinuousDistributionApproximation(double[] points, double[] weights) Construct the object using the supplied arrays of points and weights.
ContinuousDistributionApproximation(int numberOfPoints, double min, double max) Constructor for using starting values from a uniform distribution.
ContinuousDistributionApproximation(int numberOfPoints, double min, double max, double mean, double standardDeviation) Constructor for using starting values from a normal distribution.

Method Summary

Modifier and Type	Method and Description
void	setDensityAt(int index, double value)
void	setPointAt(int index, double value)
java.lang.String	toString()

Methods inherited from class com.itemanalysis.psychometrics.distribution.AbstractDistributionApproximation

evaluate, getDensityAt, getMaximum, getMean, getMinimum, getNumberOfPoints, getPointAt, getPoints, getStandardDeviation, getVariance, setNormalPointsAndWeights, setUniformPointsAndWeights, standardize

Methods inherited from class java.lang.Object

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

Constructor Detail

ContinuousDistributionApproximation

public ContinuousDistributionApproximation(int numberOfPoints,
                                           double min,
                                           double max)

Constructor for using starting values from a uniform distribution. Points and weight may be updated to something other than normal.

Parameters:

numberOfPoints - number of qudrature points

min - minimum quadrature point

max - maximum qudrature point

ContinuousDistributionApproximation

public ContinuousDistributionApproximation(int numberOfPoints,
                                           double min,
                                           double max,
                                           double mean,
                                           double standardDeviation)

Constructor for using starting values from a normal distribution. Points and weight may be updated to something other than normal.

Parameters:

numberOfPoints - number of qudrature points

min - minimum quadrature point

max - maximum qudrature point

mean - mean of normal distribution for starting values.

standardDeviation - standard deviation of normal distribution for starting values.

ContinuousDistributionApproximation

public ContinuousDistributionApproximation(double[] points,
                                           double[] weights)

Construct the object using the supplied arrays of points and weights.

Parameters:

points - discrete real points

weights - weights for the points

Method Detail

setDensityAt

public void setDensityAt(int index,
                         double value)

setPointAt

public void setPointAt(int index,
                       double value)

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object