On Thu, May 15, 2014 at 1:04 PM, rodrigo koblitz <rodrigokobl...@gmail.com> wrote: > Buenos, > I'm reading Zuur book (ecology models with R) and try make it entire in > python. > Have this function in R: > M4 <- gam(So ∼ s(De) + factor(ID), subset = I1) > > the 's' term indicated with So is modelled as a smoothing function of De > > I'm looking for something close to this in python.
The closest thing that doesn't require writing your own code is probably to use patsy's [1] support for (simple unpenalized) spline basis transformations [2]. I think using statsmodels this works like: import statsmodels.formula.api as smf # adjust '5' to taste -- bigger = wigglier, less bias, more overfitting results = smf.ols("So ~ bs(De, 5) + C(ID)", data=my_df).fit() print results.summary() To graph the resulting curve you'll want to use the results to somehow do "prediction" -- I'm not sure what the API for that looks like in statsmodels. If you need help figuring it out then the asking on the statsmodels list or stackoverflow is probably the quickest way to get help. -n [1] http://patsy.readthedocs.org/en/latest/ [2] http://patsy.readthedocs.org/en/latest/builtins-reference.html#patsy.builtins.bs -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion