/*
* InverseGaussianDistributionModel.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.inferencexml.distribution.InverseGaussianDistributionModelParser;
import dr.math.UnivariateFunction;
import dr.math.distributions.InverseGaussianDistribution;
import org.w3c.dom.Document;
import org.w3c.dom.Element;
/**
* @author Wai Lok Sibon Li
* @version $Id: InverseGaussianDistributionModel.java,v 1.8 2009/03/30 20:25:59 rambaut Exp $
*/
public class InverseGaussianDistributionModel extends AbstractModel implements ParametricDistributionModel {
/**
* @param meanParameter the mean, mu
* @param igParameter either the standard deviation parameter, sigma or the shape parameter, lamba
* @param offset offset of the distribution
* @param useShape whether shape or stdev is used
*/
public InverseGaussianDistributionModel(Parameter meanParameter, Parameter igParameter, double offset, boolean useShape) {
super(InverseGaussianDistributionModelParser.INVERSEGAUSSIAN_DISTRIBUTION_MODEL);
if(useShape) {
this.shapeParameter = igParameter;
this.stdevParameter = null;
addVariable(shapeParameter);
this.shapeParameter.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
}
else {
this.stdevParameter = igParameter;
this.shapeParameter = null;
addVariable(stdevParameter);
this.stdevParameter.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
}
this.meanParameter = meanParameter;
addVariable(meanParameter);
this.offset = offset;
this.meanParameter.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
}
public final double getS() {
if(stdevParameter==null) {
return Math.sqrt(InverseGaussianDistribution.variance(getM(), getShape()));
}
return stdevParameter.getParameterValue(0);
}
public final void setS(double S) {
if(stdevParameter==null) {
throw new RuntimeException("Standard deviation parameter is not being used");
}
else {
stdevParameter.setParameterValue(0, S);
}
}
public final Parameter getSParameter() {
if(stdevParameter==null) {
throw new RuntimeException("Standard deviation parameter is not being used");
}
return stdevParameter;
}
public final double getShape() {
if(shapeParameter == null) {
double shape = (getM() * getM() * getM()) / (getS() * getS());
return shape;
}
return shapeParameter.getParameterValue(0);
}
public final void setShape(double shape) {
if(shapeParameter==null) {
throw new RuntimeException("Shape parameter is not being used");
}
else {
shapeParameter.setParameterValue(0, shape);
}
}
public final Parameter getShapeParameter() {
if(shapeParameter==null) {
throw new RuntimeException("Shape parameter is not being used");
}
return shapeParameter;
}
/* Unused method */
//private double getStDev() {
//return Math.sqrt(InverseGaussianDistribution.variance(getM(), getShape()));//Math.sqrt((getM()*getM()*getM())/getShape());
//}
/**
* @return the mean
*/
public final double getM() {
return meanParameter.getParameterValue(0);
}
public final void setM(double M) {
meanParameter.setParameterValue(0, M);
//double shape = (getM() * getM() * getM()) / (getS() * getS());
//setShape(shape);
}
public final Parameter getMParameter() {
return meanParameter;
}
// *****************************************************************
// Interface Distribution
// *****************************************************************
public double pdf(double x) {
if (x - offset <= 0.0) return 0.0;
return InverseGaussianDistribution.pdf(x - offset, getM(), getShape());
}
public double logPdf(double x) {
if (x - offset <= 0.0) return Double.NEGATIVE_INFINITY;
return InverseGaussianDistribution.logPdf(x - offset, getM(), getShape());
}
public double cdf(double x) {
if (x - offset <= 0.0) return 0.0;
return InverseGaussianDistribution.cdf(x - offset, getM(), getShape());
}
public double quantile(double y) {
return InverseGaussianDistribution.quantile(y, getM(), getShape()) + offset;
}
/**
* @return the mean of the distribution
*/
public double mean() {
//return InverseGaussianDistribution.mean(getM(), getShape()) + offset;
return getM() + offset;
}
/**
* @return the variance of the distribution.
*/
public double variance() {
//return InverseGaussianDistribution.variance(getM(), getShape());
return getS() * getS();
}
public final UnivariateFunction getProbabilityDensityFunction() {
return pdfFunction;
}
private final UnivariateFunction pdfFunction = new UnivariateFunction() {
public final double evaluate(double x) {
System.out.println("just checking if this ever gets used anyways... probably have to change the getLowerBound in LogNormalDistributionModel if it does");
return pdf(x);
}
public final double getLowerBound() {
return 0.0;
//return Double.NEGATIVE_INFINITY;
}
public final double getUpperBound() {
return Double.POSITIVE_INFINITY;
}
};
// *****************************************************************
// Interface DensityModel
// *****************************************************************
@Override
public double logPdf(double[] x) {
return logPdf(x[0]);
}
@Override
public Variable<Double> getLocationVariable() {
throw new UnsupportedOperationException("Not implemented");
}
// *****************************************************************
// Interface Model
// *****************************************************************
public void handleModelChangedEvent(Model model, Object object, int index) {
// no intermediates need to be recalculated...
}
public 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!");
}
// **************************************************************
// Private instance variables
// **************************************************************
private final Parameter meanParameter;
private final Parameter stdevParameter;
private final Parameter shapeParameter;
private final double offset;
}