edu.umn.msi.tropix.proteomics.itraqquantitation.impl.RMethods.java Source code

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Here is the source code for edu.umn.msi.tropix.proteomics.itraqquantitation.impl.RMethods.java

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/********************************************************************************
 * Copyright (c) 2009 Regents of the University of Minnesota
 *
 * This Software was written at the Minnesota Supercomputing Institute
 * http://msi.umn.edu
 *
 * All rights reserved. The following statement of license applies
 * only to this file, and and not to the other files distributed with it
 * or derived therefrom.  This file is made available under the terms of
 * the Eclipse Public License v1.0 which accompanies this distribution,
 * and is available at http://www.eclipse.org/legal/epl-v10.html
 *
 * Contributors:
 * Minnesota Supercomputing Institute - initial API and implementation
 *******************************************************************************/

package edu.umn.msi.tropix.proteomics.itraqquantitation.impl;

import org.apache.commons.math.stat.StatUtils;

class RMethods {

    /**
     * From the following R code.
     * 
     * <pre>
     * getPvalue &lt;- function(x){
     *  x_bar &lt;- mean(x)
     *  x_std &lt;- sd(x)
     *  z &lt;- x_bar/x_std
     *  pvalue &lt;- pnorm(-abs(z)) * 2
     *  return(pvalue)
     * }
     * </pre>
     * 
     * @param x
     * @return
     */
    public static double getPValue(final double[] x) {
        final double xBar = StatUtils.mean(x);
        final double xStd = RUtils.sd(x);
        final double z = xBar / xStd;
        return RUtils.pnorm(-1 * Math.abs(z)) * 2;
    }

    /**
     * From the following R code.
     * 
     * <pre>
     * getWeightedPvalue &lt;- function(x, w){
     *  x_bar &lt;- wtd.mean(x, w)
     *  x_std &lt;- sqrt(wtd.var(x, w))
     *  z &lt;- x_bar/x_std
     *  pvalue &lt;- pnorm(-abs(z)) * 2
     *  return(pvalue)
     * }
     * </pre>
     * 
     * @param x
     * @param w
     * @return
     */
    public static double getWeightedPValue(final double[] x, final double[] w) {
        final double xBar = RUtils.weightedMean(x, w);
        final double xStd = Math.sqrt(RUtils.weightedVariance(x, w));
        final double z = xBar / xStd;
        // System.out.println(z);
        return RUtils.pnorm(-1 * Math.abs(z)) * 2;
    }

}