Created
November 18, 2011 03:40
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Linear regression in C#
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/// <summary> | |
/// Fits a line to a collection of (x,y) points. | |
/// </summary> | |
/// <param name="xVals">The x-axis values.</param> | |
/// <param name="yVals">The y-axis values.</param> | |
/// <param name="inclusiveStart">The inclusive inclusiveStart index.</param> | |
/// <param name="exclusiveEnd">The exclusive exclusiveEnd index.</param> | |
/// <param name="rsquared">The r^2 value of the line.</param> | |
/// <param name="yintercept">The y-intercept value of the line (i.e. y = ax + b, yintercept is b).</param> | |
/// <param name="slope">The slop of the line (i.e. y = ax + b, slope is a).</param> | |
public static void LinearRegression(double[] xVals, double[] yVals, | |
int inclusiveStart, int exclusiveEnd, | |
out double rsquared, out double yintercept, | |
out double slope) | |
{ | |
Debug.Assert(xVals.Length == yVals.Length); | |
double sumOfX = 0; | |
double sumOfY = 0; | |
double sumOfXSq = 0; | |
double sumOfYSq = 0; | |
double ssX = 0; | |
double ssY = 0; | |
double sumCodeviates = 0; | |
double sCo = 0; | |
double count = exclusiveEnd - inclusiveStart; | |
for (int ctr = inclusiveStart; ctr < exclusiveEnd; ctr++) | |
{ | |
double x = xVals[ctr]; | |
double y = yVals[ctr]; | |
sumCodeviates += x * y; | |
sumOfX += x; | |
sumOfY += y; | |
sumOfXSq += x * x; | |
sumOfYSq += y * y; | |
} | |
ssX = sumOfXSq - ((sumOfX * sumOfX) / count); | |
ssY = sumOfYSq - ((sumOfY * sumOfY) / count); | |
double RNumerator = (count * sumCodeviates) - (sumOfX * sumOfY); | |
double RDenom = (count * sumOfXSq - (sumOfX * sumOfX)) | |
* (count * sumOfYSq - (sumOfY * sumOfY)); | |
sCo = sumCodeviates - ((sumOfX * sumOfY) / count); | |
double meanX = sumOfX / count; | |
double meanY = sumOfY / count; | |
double dblR = RNumerator / Math.Sqrt(RDenom); | |
rsquared = dblR * dblR; | |
yintercept = meanY - ((sCo / ssX) * meanX); | |
slope = sCo / ssX; | |
} |
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