cern.jet.random

Class Empirical

java.lang.Object

cern.colt.PersistentObject

cern.jet.random.AbstractDistribution

cern.jet.random.AbstractContinousDistribution

cern.jet.random.Empirical

All Implemented Interfaces:

DoubleFunction, IntFunction, Serializable, Cloneable

public class Empirical
extends AbstractContinousDistribution

Empirical distribution.

The probability distribution function (pdf) must be provided by the user as an array of positive real numbers. The pdf does not need to be provided in the form of relative probabilities, absolute probabilities are also accepted.

If interpolationType == LINEAR_INTERPOLATION a linear interpolation within the bin is computed, resulting in a constant density within each bin.

If interpolationType == NO_INTERPOLATION no interpolation is performed and the result is a discrete distribution.

Instance methods operate on a user supplied uniform random number generator; they are unsynchronized.

Static methods operate on a default uniform random number generator; they are synchronized.

Implementation: A uniform random number is generated using a user supplied generator. The uniform number is then transformed to the user's distribution using the cumulative probability distribution constructed from the pdf. The cumulative distribution is inverted using a binary search for the nearest bin boundary.

This is a port of RandGeneral used in CLHEP 1.4.0 (C++).

Version:

1.0, 09/24/99

Author:

wolfgang.hoschek@cern.ch

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected double[]	cdf
protected int	interpolationType
static int	LINEAR_INTERPOLATION
static int	NO_INTERPOLATION

Fields inherited from class cern.jet.random.AbstractDistribution

randomGenerator

Fields inherited from class cern.colt.PersistentObject

serialVersionUID

Constructor Summary

Constructors

Constructor and Description
Empirical(double[] pdf, int interpolationType, RandomEngine randomGenerator) Constructs an Empirical distribution.

Method Summary

Methods

Modifier and Type	Method and Description
double	cdf(int k) Returns the cumulative distribution function.
Object	clone() Returns a deep copy of the receiver; the copy will produce identical sequences.
double	nextDouble() Returns a random number from the distribution.
double	pdf(double x) Returns the probability distribution function.
double	pdf(int k) Returns the probability distribution function.
void	setState(double[] pdf, int interpolationType) Sets the distribution parameters.
String	toString() Returns a String representation of the receiver.

Methods inherited from class cern.jet.random.AbstractDistribution

apply, apply, getRandomGenerator, makeDefaultGenerator, nextInt, setRandomGenerator

Methods inherited from class java.lang.Object

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

Field Detail

cdf

protected double[] cdf

interpolationType

protected int interpolationType

LINEAR_INTERPOLATION

public static final int LINEAR_INTERPOLATION

See Also:

Constant Field Values

NO_INTERPOLATION

public static final int NO_INTERPOLATION

See Also:

Constant Field Values

Constructor Detail

Empirical

public Empirical(double[] pdf,
         int interpolationType,
         RandomEngine randomGenerator)

Constructs an Empirical distribution. The probability distribution function (pdf) is an array of positive real numbers. It need not be provided in the form of relative probabilities, absolute probabilities are also accepted. The pdf must satisfy both of the following conditions

• 0.0 <= pdf[i] : 0<=i<=pdf.length-1
• 0.0 < Sum(pdf[i]) : 0<=i<=pdf.length-1

Parameters:

pdf - the probability distribution function.

interpolationType - can be either Empirical.NO_INTERPOLATION or Empirical.LINEAR_INTERPOLATION.

randomGenerator - a uniform random number generator.

Throws:

IllegalArgumentException - if at least one of the three conditions above is violated.

Method Detail

cdf

public double cdf(int k)

Returns the cumulative distribution function.

clone

public Object clone()

Returns a deep copy of the receiver; the copy will produce identical sequences. After this call has returned, the copy and the receiver have equal but separate state.

Overrides:

clone in class AbstractDistribution

Returns:

a copy of the receiver.

nextDouble

public double nextDouble()

Returns a random number from the distribution.

Specified by:

nextDouble in class AbstractDistribution

pdf

public double pdf(double x)

Returns the probability distribution function.

pdf

public double pdf(int k)

Returns the probability distribution function.

setState

public void setState(double[] pdf,
            int interpolationType)

Sets the distribution parameters. The pdf must satisfy both of the following conditions

• 0.0 <= pdf[i] : 0 < =i <= pdf.length-1
• 0.0 < Sum(pdf[i]) : 0 <=i <= pdf.length-1

Parameters:

pdf - probability distribution function.

interpolationType - can be either Empirical.NO_INTERPOLATION or Empirical.LINEAR_INTERPOLATION.

Throws:

IllegalArgumentException - if at least one of the three conditions above is violated.

toString

public String toString()

Returns a String representation of the receiver.

Overrides:

toString in class Object