Math.NET Numerics
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// <copyright file="Correlation.cs" company="Math.NET">
// Math.NET Numerics, part of the Math.NET Project
// http://numerics.mathdotnet.com
// http://github.com/mathnet/mathnet-numerics
// http://mathnetnumerics.codeplex.com
//
// Copyright (c) 2009-2010 Math.NET
//
// 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.
// </copyright>
namespace MathNet.Numerics.Statistics
{
using System;
using System.Collections.Generic;
using Properties;
/// <summary>
/// A class with correlation measures between two datasets.
/// </summary>
public static class Correlation
{
/// <summary>
/// Computes the Pearson product-moment correlation coefficient.
/// </summary>
/// <param name="dataA">Sample data A.</param>
/// <param name="dataB">Sample data B.</param>
/// <returns>The Pearson product-moment correlation coefficient.</returns>
public static double Pearson(IEnumerable<double> dataA, IEnumerable<double> dataB)
{
int n = 0;
double r = 0.0;
double meanA = dataA.Mean();
double meanB = dataB.Mean();
double sdevA = dataA.StandardDeviation();
double sdevB = dataB.StandardDeviation();
IEnumerator<double> ieA = dataA.GetEnumerator();
IEnumerator<double> ieB = dataB.GetEnumerator();
while (ieA.MoveNext())
{
if (ieB.MoveNext() == false)
{
throw new ArgumentOutOfRangeException("Datasets dataA and dataB need to have the same length.");
}
n++;
r += (ieA.Current - meanA) * (ieB.Current - meanB) / (sdevA * sdevB);
}
if (ieB.MoveNext() == true)
{
throw new ArgumentOutOfRangeException("Datasets dataA and dataB need to have the same length.");
}
return r / (n - 1);
}
}
}