All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.apache.commons.math.stat.StatUtils Maven / Gradle / Ivy

Go to download

The Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.

There is a newer version: 2.2
Show newest version
/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math.stat;

import org.apache.commons.math.MathRuntimeException;
import org.apache.commons.math.stat.descriptive.UnivariateStatistic;
import org.apache.commons.math.stat.descriptive.moment.GeometricMean;
import org.apache.commons.math.stat.descriptive.moment.Mean;
import org.apache.commons.math.stat.descriptive.moment.Variance;
import org.apache.commons.math.stat.descriptive.rank.Max;
import org.apache.commons.math.stat.descriptive.rank.Min;
import org.apache.commons.math.stat.descriptive.rank.Percentile;
import org.apache.commons.math.stat.descriptive.summary.Product;
import org.apache.commons.math.stat.descriptive.summary.Sum;
import org.apache.commons.math.stat.descriptive.summary.SumOfLogs;
import org.apache.commons.math.stat.descriptive.summary.SumOfSquares;

/**
 * StatUtils provides static methods for computing statistics based on data
 * stored in double[] arrays. 
 * 
 * @version $Revision: 772119 $ $Date: 2009-05-06 05:43:28 -0400 (Wed, 06 May 2009) $
 */
public final class StatUtils {

    /** sum */
    private static final UnivariateStatistic sum = new Sum();

    /** sumSq */
    private static final UnivariateStatistic sumSq = new SumOfSquares();

    /** prod */
    private static final UnivariateStatistic prod = new Product();

    /** sumLog */
    private static final UnivariateStatistic sumLog = new SumOfLogs();

    /** min */
    private static final UnivariateStatistic min = new Min();

    /** max */
    private static final UnivariateStatistic max = new Max();

    /** mean */
    private static final UnivariateStatistic mean = new Mean();

    /** variance */
    private static final Variance variance = new Variance();

    /** percentile */
    private static final Percentile percentile = new Percentile();
    
    /** geometric mean */
    private static final GeometricMean geometricMean = new GeometricMean();

    /**
     * Private Constructor
     */
    private StatUtils() {
    }

    /**
     * Returns the sum of the values in the input array, or
     * Double.NaN if the array is empty.
     * 

* Throws IllegalArgumentException if the input array * is null.

* * @param values array of values to sum * @return the sum of the values or Double.NaN if the array * is empty * @throws IllegalArgumentException if the array is null */ public static double sum(final double[] values) { return sum.evaluate(values); } /** * Returns the sum of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null.

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the sum of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double sum(final double[] values, final int begin, final int length) { return sum.evaluate(values, begin, length); } /** * Returns the sum of the squares of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

* * @param values input array * @return the sum of the squared values or Double.NaN if the * array is empty * @throws IllegalArgumentException if the array is null */ public static double sumSq(final double[] values) { return sumSq.evaluate(values); } /** * Returns the sum of the squares of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null.

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the sum of the squares of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double sumSq(final double[] values, final int begin, final int length) { return sumSq.evaluate(values, begin, length); } /** * Returns the product of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

* * @param values the input array * @return the product of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double product(final double[] values) { return prod.evaluate(values); } /** * Returns the product of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null.

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the product of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double product(final double[] values, final int begin, final int length) { return prod.evaluate(values, begin, length); } /** * Returns the sum of the natural logs of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

*

* See {@link org.apache.commons.math.stat.descriptive.summary.SumOfLogs}. *

* * @param values the input array * @return the sum of the natural logs of the values or Double.NaN if * the array is empty * @throws IllegalArgumentException if the array is null */ public static double sumLog(final double[] values) { return sumLog.evaluate(values); } /** * Returns the sum of the natural logs of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null.

*

* See {@link org.apache.commons.math.stat.descriptive.summary.SumOfLogs}. *

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the sum of the natural logs of the values or Double.NaN if * length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double sumLog(final double[] values, final int begin, final int length) { return sumLog.evaluate(values, begin, length); } /** * Returns the arithmetic mean of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

*

* See {@link org.apache.commons.math.stat.descriptive.moment.Mean} for * details on the computing algorithm.

* * @param values the input array * @return the mean of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double mean(final double[] values) { return mean.evaluate(values); } /** * Returns the arithmetic mean of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null.

*

* See {@link org.apache.commons.math.stat.descriptive.moment.Mean} for * details on the computing algorithm.

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the mean of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double mean(final double[] values, final int begin, final int length) { return mean.evaluate(values, begin, length); } /** * Returns the geometric mean of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

*

* See {@link org.apache.commons.math.stat.descriptive.moment.GeometricMean} * for details on the computing algorithm.

* * @param values the input array * @return the geometric mean of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double geometricMean(final double[] values) { return geometricMean.evaluate(values); } /** * Returns the geometric mean of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null.

*

* See {@link org.apache.commons.math.stat.descriptive.moment.GeometricMean} * for details on the computing algorithm.

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the geometric mean of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double geometricMean(final double[] values, final int begin, final int length) { return geometricMean.evaluate(values, begin, length); } /** * Returns the variance of the entries in the input array, or * Double.NaN if the array is empty. *

* See {@link org.apache.commons.math.stat.descriptive.moment.Variance} for * details on the computing algorithm.

*

* Returns 0 for a single-value (i.e. length = 1) sample.

*

* Throws IllegalArgumentException if the array is null.

* * @param values the input array * @return the variance of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double variance(final double[] values) { return variance.evaluate(values); } /** * Returns the variance of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* See {@link org.apache.commons.math.stat.descriptive.moment.Variance} for * details on the computing algorithm.

*

* Returns 0 for a single-value (i.e. length = 1) sample.

*

* Throws IllegalArgumentException if the array is null or the * array index parameters are not valid.

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the variance of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double variance(final double[] values, final int begin, final int length) { return variance.evaluate(values, begin, length); } /** * Returns the variance of the entries in the specified portion of * the input array, using the precomputed mean value. Returns * Double.NaN if the designated subarray is empty. *

* See {@link org.apache.commons.math.stat.descriptive.moment.Variance} for * details on the computing algorithm.

*

* The formula used assumes that the supplied mean value is the arithmetic * mean of the sample data, not a known population parameter. This method * is supplied only to save computation when the mean has already been * computed.

*

* Returns 0 for a single-value (i.e. length = 1) sample.

*

* Throws IllegalArgumentException if the array is null or the * array index parameters are not valid.

* * @param values the input array * @param mean the precomputed mean value * @param begin index of the first array element to include * @param length the number of elements to include * @return the variance of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double variance(final double[] values, final double mean, final int begin, final int length) { return variance.evaluate(values, mean, begin, length); } /** * Returns the variance of the entries in the input array, using the * precomputed mean value. Returns Double.NaN if the array * is empty. *

* See {@link org.apache.commons.math.stat.descriptive.moment.Variance} for * details on the computing algorithm.

*

* The formula used assumes that the supplied mean value is the arithmetic * mean of the sample data, not a known population parameter. This method * is supplied only to save computation when the mean has already been * computed.

*

* Returns 0 for a single-value (i.e. length = 1) sample.

*

* Throws IllegalArgumentException if the array is null.

* * @param values the input array * @param mean the precomputed mean value * @return the variance of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double variance(final double[] values, final double mean) { return variance.evaluate(values, mean); } /** * Returns the maximum of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

*

*

    *
  • The result is NaN iff all values are NaN * (i.e. NaN values have no impact on the value of the statistic).
  • *
  • If any of the values equals Double.POSITIVE_INFINITY, * the result is Double.POSITIVE_INFINITY.
  • *

* * @param values the input array * @return the maximum of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double max(final double[] values) { return max.evaluate(values); } /** * Returns the maximum of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null or * the array index parameters are not valid.

*

*

    *
  • The result is NaN iff all values are NaN * (i.e. NaN values have no impact on the value of the statistic).
  • *
  • If any of the values equals Double.POSITIVE_INFINITY, * the result is Double.POSITIVE_INFINITY.
  • *

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the maximum of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double max(final double[] values, final int begin, final int length) { return max.evaluate(values, begin, length); } /** * Returns the minimum of the entries in the input array, or * Double.NaN if the array is empty. *

* Throws IllegalArgumentException if the array is null.

*

*

    *
  • The result is NaN iff all values are NaN * (i.e. NaN values have no impact on the value of the statistic).
  • *
  • If any of the values equals Double.NEGATIVE_INFINITY, * the result is Double.NEGATIVE_INFINITY.
  • *

* * @param values the input array * @return the minimum of the values or Double.NaN if the array is empty * @throws IllegalArgumentException if the array is null */ public static double min(final double[] values) { return min.evaluate(values); } /** * Returns the minimum of the entries in the specified portion of * the input array, or Double.NaN if the designated subarray * is empty. *

* Throws IllegalArgumentException if the array is null or * the array index parameters are not valid.

*

*

    *
  • The result is NaN iff all values are NaN * (i.e. NaN values have no impact on the value of the statistic).
  • *
  • If any of the values equals Double.NEGATIVE_INFINITY, * the result is Double.NEGATIVE_INFINITY.
  • *

* * @param values the input array * @param begin index of the first array element to include * @param length the number of elements to include * @return the minimum of the values or Double.NaN if length = 0 * @throws IllegalArgumentException if the array is null or the array index * parameters are not valid */ public static double min(final double[] values, final int begin, final int length) { return min.evaluate(values, begin, length); } /** * Returns an estimate of the pth percentile of the values * in the values array. *

*

    *
  • Returns Double.NaN if values has length * 0
  • *
  • Returns (for any value of p) values[0] * if values has length 1
  • *
  • Throws IllegalArgumentException if values * is null or p is not a valid quantile value (p must be greater than 0 * and less than or equal to 100)
  • *

*

* See {@link org.apache.commons.math.stat.descriptive.rank.Percentile} for * a description of the percentile estimation algorithm used.

* * @param values input array of values * @param p the percentile value to compute * @return the percentile value or Double.NaN if the array is empty * @throws IllegalArgumentException if values is null * or p is invalid */ public static double percentile(final double[] values, final double p) { return percentile.evaluate(values,p); } /** * Returns an estimate of the pth percentile of the values * in the values array, starting with the element in (0-based) * position begin in the array and including length * values. *

*

    *
  • Returns Double.NaN if length = 0
  • *
  • Returns (for any value of p) values[begin] * if length = 1
  • *
  • Throws IllegalArgumentException if values * is null , begin or length is invalid, or * p is not a valid quantile value (p must be greater than 0 * and less than or equal to 100)
  • *

*

* See {@link org.apache.commons.math.stat.descriptive.rank.Percentile} for * a description of the percentile estimation algorithm used.

* * @param values array of input values * @param p the percentile to compute * @param begin the first (0-based) element to include in the computation * @param length the number of array elements to include * @return the percentile value * @throws IllegalArgumentException if the parameters are not valid or the * input array is null */ public static double percentile(final double[] values, final int begin, final int length, final double p) { return percentile.evaluate(values, begin, length, p); } /** * Returns the sum of the (signed) differences between corresponding elements of the * input arrays -- i.e., sum(sample1[i] - sample2[i]). * * @param sample1 the first array * @param sample2 the second array * @return sum of paired differences * @throws IllegalArgumentException if the arrays do not have the same * (positive) length */ public static double sumDifference(final double[] sample1, final double[] sample2) throws IllegalArgumentException { int n = sample1.length; if ((n != sample2.length) || (n < 1)) { throw MathRuntimeException.createIllegalArgumentException( "input arrays must have the same positive length ({0} and {1})", n, sample2.length); } double result = 0; for (int i = 0; i < n; i++) { result += sample1[i] - sample2[i]; } return result; } /** * Returns the mean of the (signed) differences between corresponding elements of the * input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length. * * @param sample1 the first array * @param sample2 the second array * @return mean of paired differences * @throws IllegalArgumentException if the arrays do not have the same * (positive) length */ public static double meanDifference(final double[] sample1, final double[] sample2) throws IllegalArgumentException { return sumDifference(sample1, sample2) / sample1.length; } /** * Returns the variance of the (signed) differences between corresponding elements of the * input arrays -- i.e., var(sample1[i] - sample2[i]). * * @param sample1 the first array * @param sample2 the second array * @param meanDifference the mean difference between corresponding entries * @see #meanDifference(double[],double[]) * @return variance of paired differences * @throws IllegalArgumentException if the arrays do not have the same * length or their common length is less than 2. */ public static double varianceDifference(final double[] sample1, final double[] sample2, double meanDifference) throws IllegalArgumentException { double sum1 = 0d; double sum2 = 0d; double diff = 0d; int n = sample1.length; if (n < 2 || n != sample2.length) { throw MathRuntimeException.createIllegalArgumentException( "input arrays must have the same length and at least two elements ({0} and {1})", n, sample2.length); } for (int i = 0; i < n; i++) { diff = sample1[i] - sample2[i]; sum1 += (diff - meanDifference) *(diff - meanDifference); sum2 += diff - meanDifference; } return (sum1 - (sum2 * sum2 / n)) / (n - 1); } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy