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Algorithms and components for machine learning and statistics.
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/*
* File: YuleSimonDistribution.java
* Authors: Kevin R. Dixon
* Company: Sandia National Laboratories
* Project: Cognitive Foundry
*
* Copyright May 30, 2010, Sandia Corporation.
* Under the terms of Contract DE-AC04-94AL85000, there is a non-exclusive
* license for use of this work by or on behalf of the U.S. Government.
* Export of this program may require a license from the United States
* Government. See CopyrightHistory.txt for complete details.
*
*/
package gov.sandia.cognition.statistics.distribution;
import gov.sandia.cognition.annotation.PublicationReference;
import gov.sandia.cognition.annotation.PublicationType;
import gov.sandia.cognition.collection.IntegerSpan;
import gov.sandia.cognition.math.MathUtil;
import gov.sandia.cognition.math.matrix.Vector;
import gov.sandia.cognition.math.matrix.VectorFactory;
import gov.sandia.cognition.statistics.AbstractClosedFormIntegerDistribution;
import gov.sandia.cognition.statistics.ClosedFormDiscreteUnivariateDistribution;
import gov.sandia.cognition.statistics.ClosedFormCumulativeDistributionFunction;
import gov.sandia.cognition.statistics.ProbabilityMassFunction;
import gov.sandia.cognition.statistics.ProbabilityMassFunctionUtil;
import java.util.Collection;
import java.util.Random;
/**
* The Yule-Simon distribution is a model of preferential attachment, such as
* a model of the number of groups follows a power-law distribution
* (Zipf's Law). That is, the PMF of a Yule-Simon distribution is a straight
* line on a semilogy plot, with the negative slope of the line determined
* by the "shape" of the distribution.
* @author Kevin R. Dixon
* @since 3.0
*/
@PublicationReference(
author="Wikipedia",
title="Yule-Simon Distribution",
type=PublicationType.WebPage,
year=2010,
url="http://en.wikipedia.org/wiki/Yule%E2%80%93Simon_distribution"
)
public class YuleSimonDistribution
extends AbstractClosedFormIntegerDistribution
implements ClosedFormDiscreteUnivariateDistribution
{
/**
* Default shape, {@value}.
*/
public static final double DEFAULT_SHAPE = 3.0;
/**
* Shape parameter, must be greater than zero
*/
protected double shape;
/**
* Creates a new instance of YuleSimonDistribution
*/
public YuleSimonDistribution()
{
this( DEFAULT_SHAPE );
}
/**
* Creates a new instance of YuleSimonDistribution
* @param shape
* Shape parameter, must be greater than zero
*/
public YuleSimonDistribution(
final double shape)
{
this.setShape(shape);
}
/**
* Copy constructor
* @param other
* YuleSimonDistribution to copy
*/
public YuleSimonDistribution(
final YuleSimonDistribution other )
{
this( other.getShape() );
}
@Override
public YuleSimonDistribution clone()
{
return (YuleSimonDistribution) super.clone();
}
/**
* Getter for shape
* @return
* Shape parameter, must be greater than zero
*/
public double getShape()
{
return this.shape;
}
/**
* Setter for shape
* @param shape
* Shape parameter, must be greater than zero
*/
public void setShape(
final double shape)
{
if( shape <= 0.0 )
{
throw new IllegalArgumentException( "Shape must be > 0.0" );
}
this.shape = shape;
}
@Override
public Double getMean()
{
return this.getMeanAsDouble();
}
@Override
public double getMeanAsDouble()
{
return this.shape / (this.shape - 1.0);
}
@Override
public double getVariance()
{
if( this.shape > 2.0 )
{
final double mean = this.getMeanAsDouble();
return mean*mean / (this.shape-2.0);
}
else
{
return 0.0;
}
}
@Override
public int sampleAsInt(
final Random random)
{
// First, generate exponential(shape)
final double u = random.nextDouble();
final double e = Math.log(u) / -this.shape;
// Next, generate geometric(Math.exp(-e))
final double geo = Math.exp(-e);
final double denom = Math.log(1.0 - geo);
final double lnu = Math.log(random.nextDouble());
return (int) Math.floor(lnu / denom) + 1;
}
@Override
public void sampleInto(
final Random random,
final int sampleCount,
final Collection output)
{
for (int i = 0; i < sampleCount; i++)
{
output.add(this.sampleAsInt(random));
}
}
@Override
public Vector convertToVector()
{
return VectorFactory.getDefault().copyValues( this.getShape() );
}
@Override
public void convertFromVector(
Vector parameters)
{
parameters.assertDimensionalityEquals(1);
this.setShape( parameters.getElement(0) );
}
@Override
public Integer getMinSupport()
{
return 1;
}
@Override
public Number getMaxSupport()
{
return Integer.MAX_VALUE;
}
@Override
public IntegerSpan getDomain()
{
double std = Math.sqrt( this.getVariance() );
final int max = (int) Math.ceil(10.0*std + 100.0);
return new IntegerSpan( this.getMinSupport(), max );
}
@Override
public int getDomainSize()
{
return this.getDomain().size();
}
@Override
public YuleSimonDistribution.PMF getProbabilityFunction()
{
return new YuleSimonDistribution.PMF( this );
}
@Override
public YuleSimonDistribution.CDF getCDF()
{
return new YuleSimonDistribution.CDF( this );
}
/**
* PMF of the Yule-Simon Distribution
*/
public static class PMF
extends YuleSimonDistribution
implements ProbabilityMassFunction
{
/**
* Creates a new instance of YuleSimonDistribution
*/
public PMF()
{
super();
}
/**
* Creates a new instance of YuleSimonDistribution
* @param shape
* Shape parameter, must be greater than zero
*/
public PMF(
final double shape)
{
super( shape );
}
/**
* Copy constructor
* @param other
* YuleSimonDistribution to copy
*/
public PMF(
final YuleSimonDistribution other )
{
super( other );
}
@Override
public double getEntropy()
{
return ProbabilityMassFunctionUtil.getEntropy(this);
}
@Override
public double logEvaluate(
final Number input)
{
final int k = input.intValue();
if( k < 1 )
{
return Math.log(0.0);
}
double logSum = 0.0;
logSum += Math.log( this.shape );
logSum += MathUtil.logBetaFunction(k, this.shape + 1.0 );
return logSum;
}
@Override
public Double evaluate(
final Number input)
{
return Math.exp( this.logEvaluate(input) );
}
@Override
public YuleSimonDistribution.PMF getProbabilityFunction()
{
return this;
}
}
/**
* CDF of the Yule-Simon Distribution
*/
public static class CDF
extends YuleSimonDistribution
implements ClosedFormCumulativeDistributionFunction
{
/**
* Creates a new instance of YuleSimonDistribution
*/
public CDF()
{
super();
}
/**
* Creates a new instance of YuleSimonDistribution
* @param shape
* Shape parameter, must be greater than zero
*/
public CDF(
final double shape)
{
super( shape );
}
/**
* Copy constructor
* @param other
* YuleSimonDistribution to copy
*/
public CDF(
final YuleSimonDistribution other )
{
super( other );
}
@Override
public Double evaluate(
final Number input)
{
final int k = input.intValue();
if( k < 1 )
{
return 0.0;
}
final double bc = Math.exp( MathUtil.logBetaFunction(k, this.shape+1.0) );
return 1.0 - k*bc;
}
@Override
public YuleSimonDistribution.CDF getCDF()
{
return this;
}
}
}