Douglas Bates wrote:
You could use the LAPACK = TRUE argument to R's qr function to get the
unconstrained pivoting scheme and use that to get coefficient
estimates according to the estimated rank of the model matrix (see
example(qr)) but that won't give you the information needed for the
analysis of variance decompositions.
Yup. However, my gut feeling is that there could be a way out:
First, how important are (sequential) ANOVA decompositions anyway; and
secondly, is it crucial that they can be read directly off the QR
decomposition? There's a lot of code that assumes that this is the case,
so you can't _easily_ plug in a pivoting QR, but the ANOVA can obviously
be obtained by other means - basically just fit the relevant sequence of
models and look at the SSD differences (as I suppose glm() must already
do for deviance tables).
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907
______________________________________________
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.
