Hello R-listers! My first post to the list is a very simple one for those who use the software continuosly. I am trying to understand the fixed-x resampling and random-x-resampling method proposed by Fox about Bootstrapping. The doubt that I have is on the side of the model run in one of the functions expressed for fixed-x resampling. What I don't understand is: X=model.matrix, and the -1 under mod= rlm. Please see below: #fixed x-resampling fit <- fitted(mod.duncan.hub) e <- residuals(mod.duncan.hub) X <- model.matrix(mod.duncan.hub) boot.huber.fixed <- function(data, indices, maxit=20){ y <- fit + e[indices] mod <- rlm(y ~ X - 1, maxit=maxit) coefficients(mod) } duncan.fix.boot <- boot(Duncan, boot.huber.fixed, 1999, maxit=100) duncan.fix.boot
I just need a quick explanation about WHAT the functions mean or do in this context. Thanks ______________________________________________ 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.