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*xM, using the least squares method. mybloggingplanet.com

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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