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Time Series Analysis in Java
There is a newer version: 0.2.1
/*
 * Copyright (c) 2016 Jacob Rachiele
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy of this software
 * and associated documentation files (the "Software"), to deal in the Software without restriction
 * including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense
 * and/or sell copies of the Software, and to permit persons to whom the Software is furnished to
 * do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all copies or
 * substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED
 * INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
 * PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
 * LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
 * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE
 * USE OR OTHER DEALINGS IN THE SOFTWARE.
 *
 * Contributors:
 *
 * Jacob Rachiele
 */
package stats;

import static data.Operators.productOf;

import java.util.Arrays;

/**
 * Static methods for computing basic statistics.
 *
 * @author Jacob Rachiele
 *
 */
public final class Statistics {
  
  private Statistics(){}

	public static double sumOf(final double[] data) {
		double sum = 0.0;
		for (double element : data) {
			sum += element;
		}
		return sum;
	}

	public static double meanOf(final double[] data) {
		final double sum = sumOf(data);
		return sum/data.length;
	}

	public static double varianceOf(final double[] data) {
		final int n = data.length;
		return sumOfSquaredDifferences(data, meanOf(data))/(n - 1);
	}

	public static double stdDeviationOf(final double[] data) {
		return Math.sqrt(varianceOf(data));
	}
	
	public static double sumOfSquared(final double[] data) {
		return sumOf(squared(data));
	}
	
	static double sumOfSquaredDifferences(final double[] data, final double point) {
		return sumOf(squared(differences(data, point)));
	}
	
	static double[] squared(final double[] data) {
		final double[] squared = new double[data.length];
		for (int i = 0; i < squared.length; i++) {
			squared[i] = data[i]*data[i];
		}
		return squared;
	}
	
	static double[] differences(final double[] data, final double point) {
		final double[] differenced = new double[data.length];
		for (int i = 0; i < differenced.length; i++) {
			differenced[i] = data[i] - point;
		}
		return differenced;
	}

	public static double covarianceOf(final double[] data, final double[] data2) {
		return sumOf(productOf(differences(data, meanOf(data)),
				differences(data2, meanOf(data2))))/(data.length-1);
	}
	
	public static double correlationOf(final double[] data, final double[] data2) {
		return covarianceOf(data, data2)/(stdDeviationOf(data)*stdDeviationOf(data2));
	}
	
	// Arrays.sort uses quicksort algorithm as of Java 8.
	public static double medianOf(final double[] data) {
		double[] sorted = data.clone();
		Arrays.sort(sorted);
		if (sorted.length % 2 == 0) {
			return (sorted[(sorted.length/2) - 1] + sorted[(sorted.length/2)]) / 2.0;
		}
		else {
			return sorted[(sorted.length - 1)/2];
		}
	}

}