NIST maintains a repository of Statistical Reference Datasets at http://www.itl.nist.gov/div898/strd/. I have been working through the datasets to compare R's results to their references with the hope that if all works well, this could become a validation package.
All the linear regression datasets give results with some degree of accuracy except one. The NIST model includes 11 parameters, but R will not compute the estimates for all 11 parameters because it finds the data matrix to be singular. The code I used is below. Any help in getting R to estimate all 11 regression parameters would be greatly appreciated. I am posting this to the R-devel list since I think that the discussion might involve the limitations of platform precision. I am using R 2.3.1 for Windows XP. rm(list=ls()) require(gsubfn) defaultPath <- "my path" data.base <- "http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA"; reg.data <- paste(data.base, "/Filip.dat", sep="") model <- "V1~V2+I(V2^2)+I(V2^3)+I(V2^4)+I(V2^5)+I(V2^6)+I(V2^7)+I(V2^8)+I(V2^9)+I (V2^10)" filePath <- paste(defaultPath, "//NISTtest.dat", sep="") download.file(reg.data, filePath, quiet=TRUE) A <- read.table(filePath, skip=60, strip.white=TRUE) lm.data <- lm(formula(model), A) lm.data Rob Carnell ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
