This algorithm for the least squares fit uses a logarithmic abscissa, and tries to find an equation matching the data set with the form y = M * log(X)/log(10) + B, using the least squares method.

The function below finds M and B, and if no solution exists, it returns 0 for both these values.

		public static void LeastSquaresFitLogAbscissa(Pnt[] points, int numPoints, ref double M, ref double B)
		{
			//Gives best fit of data to curve Y = M*log(X)/log(10) + B

			double x1, y1, xy, x2, J, LX;
			int i;

			x1 = 0.0;
			y1 = 0.0;
			xy = 0.0;
			x2 = 0.0;

			for (i = 0; i < numPoints; i++)
			{
				LX = Math.Log10(points[i].X);
				x1 = x1 + LX;
				y1 = y1 + points[i].Y;
				xy = xy + points[i].Y * LX;
				x2 = x2 + LX * LX;
			}

			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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