/*
* GammaDistributionModel.java
*
* Copyright (c) 2002-2015 Alexei Drummond, Andrew Rambaut and Marc Suchard
*
* This file is part of BEAST.
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership and licensing.
*
* BEAST is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* BEAST is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with BEAST; if not, write to the
* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
* Boston, MA 02110-1301 USA
*/
package dr.inference.distribution;
import dr.inference.model.AbstractModel;
import dr.inference.model.Model;
import dr.inference.model.Parameter;
import dr.inference.model.Variable;
import dr.math.UnivariateFunction;
import dr.math.distributions.GammaDistribution;
import org.apache.commons.math.MathException;
import org.apache.commons.math.distribution.GammaDistributionImpl;
import org.w3c.dom.Document;
import org.w3c.dom.Element;
/**
* A class that acts as a model for gamma distributed data.
*
* @author Andrew Rambaut
* @author Alexei Drummond
* @version $Id: GammaDistributionModel.java,v 1.6 2005/05/24 20:25:59 rambaut Exp $
*/
public class GammaDistributionModel extends AbstractModel implements ParametricDistributionModel {
public enum GammaParameterizationType {
ShapeScale,
ShapeRate,
ShapeMean,
OneParameter
}
public static final String GAMMA_DISTRIBUTION_MODEL = "gammaDistributionModel";
public static final String ONE_P_GAMMA_DISTRIBUTION_MODEL = "onePGammaDistributionModel";
/**
* Construct a gamma distribution model with a default shape scale parameterization.
*/
public GammaDistributionModel(Variable<Double> shape, Variable<Double> scale) {
this(GammaParameterizationType.ShapeScale, shape, scale, 0.0);
}
/**
* Construct a one parameter gamma distribution model.
*/
public GammaDistributionModel(Variable<Double> shape) {
this(GammaParameterizationType.OneParameter, shape, null, 0.0);
}
/**
* Construct a gamma distribution model.
*/
public GammaDistributionModel(GammaParameterizationType parameterization, Variable<Double> shape, Variable<Double> parameter2, double offset) {
super(GAMMA_DISTRIBUTION_MODEL);
this.offset = offset;
this.parameterization = parameterization;
this.shape = shape;
addVariable(shape);
shape.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
switch (parameterization) {
case ShapeScale:
this.scale = parameter2;
addVariable(scale);
scale.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
rate = null;
mean = null;
break;
case ShapeRate:
this.rate = parameter2;
addVariable(rate);
rate.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
scale = null;
mean = null;
break;
case ShapeMean:
this.mean = parameter2;
addVariable(mean);
mean.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
scale = null;
rate = null;
break;
case OneParameter:
scale = null;
rate = null;
mean = null;
break;
default:
throw new IllegalArgumentException("Unknown parameterization type");
}
}
// *****************************************************************
// Interface Distribution
// *****************************************************************
public double pdf(double x) {
if (x < offset) return 0.0;
return GammaDistribution.pdf(x - offset, getShape(), getScale());
}
public double logPdf(double x) {
if (x < offset) return Double.NEGATIVE_INFINITY;
return GammaDistribution.logPdf(x - offset, getShape(), getScale());
}
public double cdf(double x) {
if (x < offset) return 0.0;
return GammaDistribution.cdf(x - offset, getShape(), getScale());
}
public double quantile(double y) {
try {
return (new GammaDistributionImpl(getShape(), getScale())).inverseCumulativeProbability(y) + offset;
} catch (MathException e) {
return Double.NaN;
}
}
public double mean() {
return GammaDistribution.mean(getShape(), getScale()) + offset;
}
public double variance() {
return GammaDistribution.variance(getShape(), getScale());
}
public final UnivariateFunction getProbabilityDensityFunction() {
return pdfFunction;
}
private final UnivariateFunction pdfFunction = new UnivariateFunction() {
public final double evaluate(double x) {
return pdf(x);
}
public final double getLowerBound() {
return offset;
}
public final double getUpperBound() {
return Double.POSITIVE_INFINITY;
}
};
// *****************************************************************
// Interface Model
// *****************************************************************
public void handleModelChangedEvent(Model model, Object object, int index) {
// no intermediates need to be recalculated...
}
protected final void handleVariableChangedEvent(Variable variable, int index, Parameter.ChangeType type) {
// no intermediates need to be recalculated...
}
protected void storeState() {
} // no additional state needs storing
protected void restoreState() {
} // no additional state needs restoring
protected void acceptState() {
} // no additional state needs accepting
// **************************************************************
// XMLElement IMPLEMENTATION
// **************************************************************
public Element createElement(Document document) {
throw new RuntimeException("Not implemented!");
}
public double getShape() {
return shape.getValue(0);
}
public double getScale() {
switch (parameterization) {
case ShapeScale:
return scale.getValue(0);
case ShapeRate:
return (1.0 / rate.getValue(0));
case ShapeMean:
return (mean.getValue(0) / getShape());
case OneParameter:
return (1.0 / getShape());
default:
throw new IllegalArgumentException("Unknown parameterization type");
}
}
// *****************************************************************
// Interface DensityModel
// *****************************************************************
@Override
public double logPdf(double[] x) {
return logPdf(x[0]);
}
@Override
public Variable<Double> getLocationVariable() {
throw new UnsupportedOperationException("Not implemented");
}
// **************************************************************
// Private instance variables
// **************************************************************
private final GammaParameterizationType parameterization;
private final Variable<Double> shape;
private final Variable<Double> scale;
private final Variable<Double> rate;
private final Variable<Double> mean;
private final double offset;
}