<< repost because previous attempt was not plain text, sorry! >>
Hi Folks, I have a pretty simple problem: after building a multivariate linear model, I need to report my 95% confidence interval for predictions based on future observations. I know that one option is to use predict(interval="prediction") but I'm curious about less parametric ways to get an estimate. I tried doing K-fold cross validation using cv.lm() from the DAAG package, but it currently only uses the first independent variable in the provided linear model. No warnings or anything. There was a thread about this here about 3 years ago but the person got no response. Does anyone know of a working alternative? Thanks, Dan ______________________________________________ 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.
