[R] glm.fit to use LAPACK instead of LINPACK
rvaradhan at jhmi.edu
Thu Oct 22 17:26:11 CEST 2009
LAPACK is newer and is supposed to contain better algorithms than LINPACK. It is not true that LAPACK cannot handle rank-deficient problems. It can.
However, I do not know if using LAPACK in glm.fit instead of LINPACK would be faster and/or more memory efficient.
Ravi Varadhan, Ph.D.
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvaradhan at jhmi.edu
----- Original Message -----
From: Ted <tchiang at sickkids.ca>
Date: Thursday, October 22, 2009 10:53 am
Subject: Re: [R] glm.fit to use LAPACK instead of LINPACK
To: "r-help at R-project.org" <r-help at r-project.org>
> I understand that the glm.fit calls LINPACK fortran routines instead of
> LAPACK because it can handle the 'rank deficiency problem'. If my data
> matrix is not rank deficient, would a glm.fit function which runs on
> LAPACK be faster? Would this be worthwhile to convert glm.fit to use
> LAPACK? Has anyone done this already?? What is the best way to do this?
> I'm looking at very large datasets (thousands of glm calls), and would
> like to know if it's worth the effort for performance issues.
> Ted Chiang
> Bioinformatics Analyst
> Centre for Computational Biology
> Hospital for Sick Children, Toronto
> tchiang at sickkids.ca
> R-help at r-project.org mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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