> > 3) Or: is there already a straight-forward least-square fitting algorithm > for polynomials? Have a look: http://www.nr.com/ or http://wwwinfo.cern.ch/asdoc/cernlib.html or http://wwwinfo.cern.ch/asd/lhc++/Nag_Fortran/mk18.htm I mean sometimes it is much much faster and better to call some well-known and well-tested Fortran subroutine to solve YOUR problem from C++ code rather looking for "the good for all" the object model of "the vector / matrix ". I think the best ( well-defined at least) object model of those are just an array of the floating (single or double) point numbers (why not ?) and the best method of such "virtual class" is some Fortran (converted to C may be) subroutine. At least very this sort of model (C++ class) should be implemented first. Lacking C++ class for the "trivial" vector / matrix object model (with a trivial pointer to the trivial plain array as its data-member) caused 97 % of the problem we are fighting with. I mean very often it is much cheaper to collect one's data one re-distributed across his/her object model into the single array and call well-known and tested numerical code Try. I believe it will take you much less time ( 1 day at most) the get the result rather seeking / learning / debugging / deriving / implementing and adjusting your data model to fit that universal C++_class_vector_matrix object model. (Ohh. well I forgot then you will fight a problem how to save / store your results and transfer it to somebody ) Do not forget all future readers of your code (and you yourself included) must keep in mind what the statement c = a*b; really does. (Is it cross product or scalar one, for example ) Hope this helps, With my best regards, Valery
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