Hi Philipp, GSL has multivariate linear regression too: http://www.gnu.org/software/gsl/manual/html_node/Multi_002dparameter-fitting.html
Barrett On Saturday 13 December 2008, Philipp Klaus Krause wrote: > I want to do a least squares fit of a line in 3 or 4-dimensional space > to 16 data points. > I looked at the manual, it seems gsl provides least squares linear fits > only for onedimensional stuff. > The classic way would be the principal component analysis (PCA), again > gsl does not provide this. PCA can be done by estimating the covariance > matrix and getting thet eigenvector for the biggest eigenvalue. gsl > seems to provide functions to get the eigenvalues and vectors, it even > sorts them for me. It might be a bit inefficient to calculate them all > when I need only the biggest, but that shouldn't be much of a problem. > However gsl seems to provide estimation of covariance only in one > dimension, so I would have to implement estimation of the covariance > matrix myself. > Is this correct? Will performance be okay for such small data sets (16 > data points, in 3 or 4 dimensions) or is gsl optimized too much towards > "bigger" problems? > > Philipp > > > > _______________________________________________ > Help-gsl mailing list > Help-gsl@gnu.org > http://lists.gnu.org/mailman/listinfo/help-gsl _______________________________________________ Help-gsl mailing list Help-gsl@gnu.org http://lists.gnu.org/mailman/listinfo/help-gsl
