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.

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;
}
}
```