McGehee, Robert writes: > dataSet <- data.frame(y = vol[, 12]) > dataSet$X <- data.matrix(vol[, 1:11]) > > ans.pcr <- pcr(y ~ X, 6, data = dataSet, validation = "CV") > > If there's a more elegant way of doing this without using data frames of > matrices, I'd be interested as well.
I actually find using data frames with matrices the most elegant way. :-) Especially if you have several matrices. Alternatively, to regress one variable of a data frame on the rest of the variables, one can use ans.pcr <- pcr(y ~ ., 6, data = vol, validation = "CV") (assuming the response variable is called `y' in the data frame; see names(vol).) One does not _have_ to store the data in a data frame (although I would recommend it, because it is then easier to specify test data sets and alternative data sets). One can simply store the variables in the global environment, and skip the `data' argument of `pcr', -- HTH, Bjørn-Helge Mevik ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
