Hello I am trying to use all subsets regression on a test dataset consisting of 11 trails and 46 potential predictor variables. I would like to use Mallow's Cp as a selection criterion. The leaps function would provide the required output but does not work with this many variables (see below). The alternative function regsubsets should be used, but I am not able to define the function in such a way that is gives satisfactory results.
library(leaps) data <- read.table('C:/test_plot_sum2.txt', header = TRUE) attach(data) nox <- data[,1] cnt <- data[,2] vars <- data[,3:48] leaps.setup(x = vars, y = nox, wt = cnt, nvmax = 1) leaps(x = vars, y = nox, wt = cnt, method = "Cp", nbest = 2, names = names(vars)) Error in leaps(x = vars, y = nox, wt = cnt, method = "Cp", nbest = 2, : leaps does not allow more than 31 variables; use regsubsets() regsubsets(x = vars, y = nox, weights = cnt, method = "seqrep", nbest = 1, names = names(vars), nvmax = 3) 1 subsets of each size up to 4 Selection Algorithm: 'sequential replacement' Warning message: 37 linear dependencies found in: leaps.setup(x, y, wt = weights, nbest = nbest, nvmax = nvmax, Is there someone who could shine a few rays of light on this? Many thanks for your assistance. Kind regards, Robin Smit This e-mail and its contents are subject to the DISCLAIMER at http://www.tno.nl/disclaimer/email.html [[alternative HTML version deleted]] ______________________________________________ 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