/* * 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; }