[SciPy-dev] some statistical models / formulas
Jonathan Taylor
jonathan.taylor at stanford.edu
Wed Apr 19 18:16:17 CDT 2006
i have made a numpy/scipy package for some linear statistical models
http://www-stat.stanford.edu/~jtaylo/scipy_stats_models-0.01a.tar.gz
i was hoping that it might someday get into scipy.stats, maybe as
scipy.stats.models?
anyways, i am sure the code needs work and more docs with examples, but
right now there is basic functionality for the following (the tests give
some examples):
- model formulae as in R (to some extent)
- OLS (ordinary least square regression)
- WLS (weighted least square regression)
- AR1 regression (non-diagonal covariance -- right now just AR1 but easy
to extend to ARp)
- generalized linear models (all of R's links and variance functions but
extensible as well -- not everything has been rigorously tested but
logistic agrees with R, for instance)
- robust linear models using M estimators (with a number of standard
default robust norms as in R's rlm)
- robust scale estimates (MAD, Huber's proposal 2).
it would be nice to add a few things over time, too, like:
- mixed effects models
- generalized additive models (gam), generalized estimating equations
(gee)....
- nonlinear regression (i have some quasi working code for this, too,
but it is not yet included).
+ anything else people want to add.
-- jonathan
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