Least squares, matrix divide

x lsq y     lsq[x;y]

Where:

• x and y are float matrixes with the same number of columns
• the number of rows of y do not exceed the number of columns
• the rows of y are linearly independent

returns the least-squares solution of x = (x lsq y) mmu y. That is, if

d:x - (x lsq y) mmu y

then sum d*d is minimized. If y is a square matrix, d is the zero matrix, up to rounding errors.