I need to find the best fitting regression line for a set of points. For example for this matrix:
int b [][] = { { 3, 1, 0, 0, 0, 0, 0, 0, 0 },
{ 1, 2, 3, 1, 0, 1, 0, 0, 0 },
{ 0, 1, 2, 1, 0, 0, 0, 0, 0 },
{ 0, 0, 0, 3, 0, 0, 0, 0, 0 },
{ 0, 0, 0, 0, 0, 0, 0, 0, 0 },
{ 0, 0, 0, 0, 0, 1, 3, 0, 0 },
{ 0, 0, 0, 0, 0, 1, 2, 3, 1 },
{ 0, 0, 0, 0, 0, 1, 1, 1, 2 },
{ 0, 0, 0, 0, 0, 0, 0, 0, 1 } };
Every number represents the amount of data points (weight I suppose) at that location (where rows are the X axis and Columns are for the Y). I have attempted to use the SimpleRegression class from the apache mathematics library and am having some issues. First, it doesn't appear to support weights. Second I believe that I'm doing something wrong, even for a matrix that is nothing but 1's on the main diagonal the slope/intercept results make no sense.
public static void main(String[] args) {
double a[][] = new double[9][9];
for (int i = 0; i < 9; i++)
a[i][i] = 1;
SimpleRegression r = new SimpleRegression(true);
r.addData(a);
System.out.println("Slope = " + r.getSlope());
System.out.println("Intercept = " + r.getIntercept());
}
This gives me results that are incorrect. I would assume that this matrix represents the function f(x) = x yet the slope I'm getting is -0.12499..
Could anyone point me at what I'm doing wrong? I have a feeling I'm not only misusing the code but also the mathematics.