From CarnellR at BATTELLE.ORG  Mon Jul 31 01:42:29 2006
From: CarnellR at BATTELLE.ORG (Carnell, Rob C)
Date: Sun, 30 Jul 2006 19:42:29 -0400
Subject: [Rd] NIST StRD linear regression
Message-ID: <0F923E9EBBF1554ABA641ACA04BEBEC0051BD9FE@WS-BCO-MSE7.milky-way.battelle.org>

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



[Rd] NIST StRD linear regression
Carnell, Rob C