Good Day, I fit a multivariate linear regression model with 3 dependent variables and several predictors using the lm function. I would like to use stepwise variable selection to produce a set of candidate models. However, when I pass the fitted lm object to step() I get the following error:
Error from R: Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, : no 'drop1' method for "mlm" models My dependent data is in the matrix ymat where ymat is 35 rows by 3 columns. The predictors are in X where X is 35 by 6 The steps I used were: m.fit <- lm(ymat ~ ., data=X) m.step <- step(m.fit) If variable selection is not possible with step() is there another package that will perform variable selection in a multivariate setting? System information: platform x86_64-apple-darwin9.8.0 arch x86_64 os darwin9.8.0 system x86_64, darwin9.8.0 status major 2 minor 13.1 year 2011 month 07 day 08 svn rev 56322 language R version.string R version 2.13.1 (2011-07-08) Thanks in advance. ______________________________________________ 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.
