Hello and thanks for your reply, but as you said, this is not really what I'm trying to do. My purpose is not one of variable selection within a model with multiple predictors, but simply fitting a large number of models with only one predictor. I was just hoping there would be a solution as simple as the one given in my example which gives the results of many regression models of the type Yi~x where i spans all the colums in a matrix and x is one predictor. My objective being the fitting of many regression models of the type y~Xi where i spans all the columns in a matrix and y is one dependent variable.
Best regards, David Gouache ARVALIS - Institut du végétal Station de La Minière 78280 Guyancourt Tel: 01.30.12.96.22 / Port: 06.86.08.94.32 -----Message d'origine----- De : Greg Snow [mailto:greg.s...@imail.org] Envoyé : mardi 24 février 2009 18:22 À : GOUACHE David; r-h...@stat.math.ethz.ch Objet : RE: multiple regressions on columns The add1 function might be what you want, there is also addterm in the MASS package and the leaps package can do some things along this line (plus more). But before doing this, you may want to ask yourself what question you are really trying to answer, then explore if this answers that question or not. -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.s...@imail.org 801.408.8111 > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r- > project.org] On Behalf Of GOUACHE David > Sent: Tuesday, February 24, 2009 10:13 AM > To: r-h...@stat.math.ethz.ch > Subject: [R] multiple regressions on columns > > R-helpers, > > A quick question regarding my wanting to run multiple regressions > without writing a loop. > Looking at a previous discussion : > http://tolstoy.newcastle.edu.au/R/e2/help/07/02/9740.html > > my objective is to do the "opposite", i.e. instead of having the same > independent variable and testing it against multiple dependent > variables, my goal is to test multiple independent variables against > the same dependent variable. > > Using the iris dataset: > > iris4 <- as.matrix(iris[,-c(1,5)]) > summary(lm(iris4 ~ Sepal.Length, iris)) > > what I would have liked is to do the following : > > summary(lm(Sepal.Length ~ iris4, iris)) > > and obtain the results from 3 separate regressions, as above, instead > of one multiple regression... > > Any clues ? > > Tanks in advance > > David Gouache > ARVALIS - Institut du végétal > Station de La Minière > 78280 Guyancourt > Tel: 01.30.12.96.22 / Port: 06.86.08.94.32 > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
