The train function in the caret package will do this. The trainControl function would use method ="repeatedcv" and repeats = 100.
On Feb 18, 2012, at 2:15 PM, Greg Snow <538...@gmail.com> wrote: > The validate function in the rms package can do cross validation of > ols objects (ols is similar to lm, but with additional information), > the default is to do bootstrap validation, but you can specify > crossvalidation instead. > > On Thu, Feb 16, 2012 at 10:44 AM, samuel-rosa > <alessandrosam...@yahoo.com.br> wrote: >> Dear R users >> >> I'd like to hear from someone if there is a function to do a repeated k-fold >> cross-validation for a lm object and get the predicted values for every >> observation. The situation is as follows: >> I had a data set composed by 174 observations from which I sampled randomly >> a subset composed by 150 observations. With the subset (n = 150) I fitted >> the model: y = a + bx. The model validation has to be done using a repeated >> k-fold cross-validation on the complete data set (n = 174). I need to use 10 >> folds and repeat the cross-validation 100 times. In the end of the >> procedure, I need to have access to the predicted values for each >> observation, that is, to the 100 predicted values for each observation. The >> function lmCV() in the package chemometrics provides the predicted values. >> However, it works only with multiple linear regression models. >> I hope there is a way of doing it. >> Best regards, >> >> ----- >> Bc.Sc.Agri. Alessandro Samuel-Rosa >> Postgraduate Program in Soil Science >> Federal University of Santa Maria >> Av. Roraima, nÂș 1000, Bairro Camobi, CEP 97105-970 >> Santa Maria, Rio Grande do Sul, Brazil >> -- >> View this message in context: >> http://r.789695.n4.nabble.com/Repeated-cross-validation-for-a-lm-object-tp4394833p4394833.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ >> 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. > > > > -- > Gregory (Greg) L. Snow Ph.D. > 538...@gmail.com > > ______________________________________________ > 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.