It's called ols in PDL::Stats::GLM for Ordinary Least Squares regression, because the name "linear" was taken when I wrote the function. Either ols<http://pdl-stats.sourceforge.net/GLM.htm#ols>or ols_t <http://pdl-stats.sourceforge.net/GLM.htm#ols_t> (threaded version) can work.
Best, Maggie On Mon, May 6, 2013 at 8:48 AM, Joel Berger <[email protected]> wrote: > I use PDL::Fit::LM all the time, works well for me! > > > On Mon, May 6, 2013 at 7:36 AM, Ingo Schmid <[email protected]> wrote: > >> Hi, >> >> I know there are >> >> PDl::Fit::Linfit >> PDL::Stats::GLM >> PDL::Fit::LM >> >> At least one of those should be able to do what you need, I guess. >> >> Ingo >> >> On 05/06/2013 02:24 PM, John Lapeyre wrote: >> > >> > ... I was using fitpoly1d incorrectly! Now it is fast >> > enough. Still, a simpler routine with no extra dependencies >> > would be useful. >> > >> > John >> > >> > >> > _______________________________________________ >> > Perldl mailing list >> > [email protected] >> > http://mailman.jach.hawaii.edu/mailman/listinfo/perldl >> > >> >> >> _______________________________________________ >> Perldl mailing list >> [email protected] >> http://mailman.jach.hawaii.edu/mailman/listinfo/perldl >> > > > _______________________________________________ > Perldl mailing list > [email protected] > http://mailman.jach.hawaii.edu/mailman/listinfo/perldl > >
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