[SciPy-user] 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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Jonathan Taylor                           Tel:   650.723.9230
Dept. of Statistics                       Fax:   650.725.8977
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