We have already looked at several other ways of doing a least squares fit to find an quation representing a set of data. We now look at the least squares fit using full logs, which tries to match the data with the equation y = B*x^{M}, using the least squares method.

As with the previous least squares functions, the function below returns the calculated values for M and B, and if no solution exists returns 0 for both of them.

public static void LeastSquaresFitLogFull(Pnt[] points, int numPoints, ref double M, ref double B) { //Gives best fit of data to curve Y = B*X^M double x1, y1, xy, x2, J; double[] LX = new double[numPoints]; double[] LY = new double[numPoints]; int i; x1 = 0.0; y1 = 0.0; xy = 0.0; x2 = 0.0; for (i = 0; i < numPoints; i++) { LX[i] = Math.Log10(points[i].X); LY[i] = Math.Log10(points[i].Y); x1 = x1 + LX[i]; y1 = y1 + LY[i]; xy = xy + LY[i] * LX[i]; x2 = x2 + LX[i] * LX[i]; } J = ((double)numPoints * x2) - (x1 * x1); if (J != 0.0) { M = (((double)numPoints * xy) - (x1 * y1)) / J; M = Math.Floor(1.0E3 * M + 0.5) / 1.0E3; B = ((y1 * x2) - (x1 * xy)) / J; B = Math.Floor(1.0E3 * B + 0.5) / 1.0E3; } else { M = 0; B = 0; } }

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