Hi If you do not insist on matrix and use data frame instead
lapply(iris4,function(x) lm(iris$Sepal.Length~x)) can do it Regards Petr r-help-boun...@r-project.org napsal dne 25.02.2009 09:56:25: > 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. ______________________________________________ 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.
