Hi Pierre, I got lost in the flurry of questions and replies: 1) Is your matrix not positive definite involving density prob. ?? if so why ?? 2) Valeri points you to Cholesky decomposition routines which are no different than the TMatrixD::InvertPosDef() routine. I would suggest to make use of the TMatrix class function if you already have your data stored in it. Eddy > > Hi, > > my matrix is not only positive... > > Pierre-Luc Drouin > > On Sat, 12 Jul 2003, Eddy Offermann wrote: > > > Hi Pierre, > > > > Your matrix is probably not only symmetric but also postive definite (x^T A x >= 0) > > For this case the TMatrixD::InvertPosDef() is the best choice. > > Determinant is calculated through Double_t TMatrixD::Determinant(). > > > > Eddy > > > > > > > > Hello, > > > > > > I've to compute the determinant and to invert a matrix in order to > > > evaluate density probabilities in a multi-gaussian distribution. So the > > > matrix is symmetric, and diagonal terms are 2-3 order of magnitudes bigger > > > than off-diagnoal terms. I want to minimize the error of truncature on > > > determinant and inverse matrix. What should I use instead of > > > TMatrix::Invert ? > > > > > > Thank you! > > > > > > Pierre-Luc Drouin > > > > > >
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