Constraint on coefficient when fitting with lm, glm etc ...

An embedded and charset-unspecified text was scrubbed...
Name: not available
Url: https://stat.ethz.ch/pipermail/r-help/attachments/20051208/a3cfbd5f/attachment.pl
I've just answered a similar question from Richard O'Keefe.

MASS p.445 shows you how to do this for logistic regression, and the 
example is easy to modify.

Dear R-users,

I would like to know if there is any way to constraints optimized parameters
using the function lm, glm or others that are written in the form:
Lm( formula, data ...)
As I understand, formula are of the type y ~ X1 +X2+ ... Xi (where Y, X1, X2
..Xi are vectors). In my case I would like the estimates of this linear
combination computed with lm to be positives.
I haven't found anything about it in the documentation, I would like to use
the lm.ridge function with positives estimates.
Would anyone have already met this problem ?

Thank you,

  Emmanuel

	[[alternative HTML version deleted]]

______________________________________________
R-help at stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html

Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595