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.