[SciPy-user] Any SPLUS to scipy ideas for lm and summary(lm)?
webb.sprague at gmail.com
Mon Apr 10 13:40:46 CDT 2006
I would like to duplicate the following piece of SPLUS/R code in
Python-scipy, and would love somebody smarter than me to give me some
ideas. (If you don't know SPLUS/R, you may not want to bother with
model.kt <- summary(lm(kt.diff ~ 1 ))
kt.drift <- model.kt$coefficients[1,1] # Coefficient
sec <- model.kt$coefficients[1,2] # Standard Error of the Coefficient (SEC)
see <- model.kt$sigma # Standard error of the Equation (SEE)
Getting a least-squares fit in scipy is not a problem, but getting all
that other nice stuff IS kind of a problem. I don't mind either
hacking scipy.stats, or writing my own function, but maybe someone has
some ideas for this, maybe it can be contributed, or ???. I also
realize that the SPLUS formula notation doesn't exist at all in
scipy-Python, so no need to point that out to me.
Perhaps there should be a scipy.stats working group? It seems like
scipy.stats (not including the probability distributions and basic
summary functions, which are fine) is kind of a forgotten stepchild in
scipy, and probably needs a nurturing aunt or uncle or several....
Thx, sorry for such an open ended question.
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