mdiggory 2003/06/17 15:55:39 Added: math/src/java/org/apache/commons/math/stat StatUtils.java Log: Initial Addition of StatUtils. Some methods need review, implementation and possibly debugging Revision Changes Path 1.1 jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/StatUtils.java Index: StatUtils.java =================================================================== /* ==================================================================== * The Apache Software License, Version 1.1 * * Copyright (c) 2003 The Apache Software Foundation. All rights * reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in * the documentation and/or other materials provided with the * distribution. * * 3. The end-user documentation included with the redistribution, if * any, must include the following acknowlegement: * "This product includes software developed by the * Apache Software Foundation (http://www.apache.org/)." * Alternately, this acknowlegement may appear in the software itself, * if and wherever such third-party acknowlegements normally appear. * * 4. The names "The Jakarta Project", "Commons", and "Apache Software * Foundation" must not be used to endorse or promote products derived * from this software without prior written permission. For written * permission, please contact [EMAIL PROTECTED] * * 5. Products derived from this software may not be called "Apache" * nor may "Apache" appear in their names without prior written * permission of the Apache Software Foundation. * * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF * SUCH DAMAGE. * ==================================================================== * * This software consists of voluntary contributions made by many * individuals on behalf of the Apache Software Foundation. For more * information on the Apache Software Foundation, please see * <http://www.apache.org/>. */ package org.apache.commons.math.stat; /** * StatUtils provides easy static implementations of common double[] based * statistical methods. These return a single result value or in some cases, as * identified in the javadoc for each method, Double.NaN. * * @author <a href="mailto:[EMAIL PROTECTED]">Mark Diggory</a> */ public class StatUtils { /** * The sum of the values that have been added to Univariate. * @param values Is a double[] containing the values * @return the sum of the values or Double.NaN if the array is empty */ public static double sum(double[] values) { double accum = 0.0; for (int i = 0; i < values.length; i++) { accum += values[i]; } return accum; } /** * Returns the sum of the squares of the available values. * @param values Is a double[] containing the values * @return the sum of the squared values or Double.NaN if the array is empty */ public static double sumSq(double[] values) { double accum = 0.0; for (int i = 0; i < values.length; i++) { accum += Math.pow(values[i], 2.0); } return accum; } /** * Returns the <a href=http://www.xycoon.com/arithmetic_mean.htm> * arithmetic mean </a> of the available values * @param values Is a double[] containing the values * @return the mean of the values or Double.NaN if the array is empty */ public static double mean(double[] values) { return sum(values) / values.length; } /** * * @param values Is a double[] containing the values * @return the result, Double.NaN if no values for an empty array * or 0.0 for a single value set. */ public static double standardDeviation(double[] values) { double stdDev = Double.NaN; if (values.length != 0) { stdDev = Math.sqrt(variance(values)); } return (stdDev); } /** * Returns the variance of the available values. * @param values Is a double[] containing the values * @return the result, Double.NaN if no values for an empty array * or 0.0 for a single value set. */ public static double variance(double[] values) { double variance = Double.NaN; if (values.length == 1) { variance = 0; } else if (values.length > 1) { double mean = mean(values); double accum = 0.0; for (int i = 0; i < values.length; i++) { accum += Math.pow((values[i] - mean), 2.0); } variance = accum / (values.length - 1); } return variance; } /** * Returns the skewness of a collection of values. Skewness is a * measure of the assymetry of a given distribution. * @param values Is a double[] containing the values * @return the skewness of the values or Double.NaN if the array is empty */ public double skewness(double[] values) { // Initialize the skewness double skewness = Double.NaN; // Get the mean and the standard deviation double mean = mean(values); double stdDev = standardDeviation(values); // Sum the cubes of the distance from the mean divided by the // standard deviation double accum = 0.0; for (int i = 0; i < values.length; i++) { accum += Math.pow((values[i] - mean) / stdDev, 3.0); } // Get N double n = values.length; // Calculate skewness skewness = (n / ((n - 1) * (n - 2))) * accum; return skewness; } /** * Returns the kurtosis for this collection of values. Kurtosis is a * measure of the "peakedness" of a distribution. * @param values Is a double[] containing the values * @return the kurtosis of the values or Double.NaN if the array is empty */ public double kurtosis(double[] values) { // Initialize the kurtosis double kurtosis = Double.NaN; // Get the mean and the standard deviation double mean = mean(values); double stdDev = standardDeviation(values); // Sum the ^4 of the distance from the mean divided by the // standard deviation double accum = 0.0; for (int i = 0; i < values.length; i++) { accum += Math.pow((values[i] - mean) / stdDev, 4.0); } // Get N double n = values.length; double coefficientOne = (n * (n + 1)) / ((n - 1) * (n - 2) * (n - 3)); double termTwo = ((3 * Math.pow(n - 1, 2.0)) / ((n - 2) * (n - 3))); // Calculate kurtosis kurtosis = (coefficientOne * accum) - termTwo; return kurtosis; } /** * Returns the maximum of the available values * @param values Is a double[] containing the values * @return the maximum of the values or Double.NaN if the array is empty */ public static double max(double[] values) { double max = Double.NaN; for (int i = 0; i < values.length; i++) { if (i == 0) { max = values[i]; } else { max = Math.max(max, values[i]); } } return max; } /** * Returns the minimum of the available values * @param values Is a double[] containing the values * @return the minimum of the values or Double.NaN if the array is empty */ public static double min(double[] values) { double min = Double.NaN; for (int i = 0; i < values.length; i++) { if (i == 0) { min = values[i]; } else { min = Math.min(min, values[i]); } } return min; } /** * Returns the mode of the values that have been added. The mode is * the element which occurs with the most frequency * @return the mode */ public static double mode(){ // Mode depends on a refactor Freq class String msg = "mode() is not yet implemented"; throw new UnsupportedOperationException(msg); } /** * Returns the mode of the values that have been added. The mode is * the element which occurs with the most frequency * @return the mode */ public static double median(double[] values){ // Mode depends on a refactor Freq class String msg = "median() is not yet implemented"; throw new UnsupportedOperationException(msg); } }
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