Hi all, I'm writing a polynomial fitting routine, using the least squares approximation, but I'm encountering some difficulties with the matrix-inversion. It seems that the problem is sensitive for numerical roudoff's. Of course, using the fitting functionality of ROOT is still an alternative, but if anyone knows the answers to the following, please let me know. 1) Is there an improved version TMatrix, in double precision?? 2) Does anyone know a standard routine for calculating the binomial coeefficients (i.e. n over k, the number of permutions of k things in a pool of n: n!/(k!*(n-k)!) ) 3) Or: is there already a straight-forward least-square fitting algorithm for polynomials? Thanks, Marco van Leeuwen
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