Hi Mark,
I am interested in doing what you are asking about. Did you figure out an
easy way to do this. I am interested in performing many two and more
factor anova on a dataframe. I am still a little new to R but I know enough
to get me this far.
thanks
Don
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Hi Mark,
Unless you are fitting millions of very very very simple models, I
doubt that extracting p-values is going to be a limiting factor in the
speed of your analysis.
Hadley
On Mon, Mar 8, 2010 at 3:47 AM, Mark Kimpel wrote:
> Hadley,
>
> Thanks for pointing me to some good articles. Unfort
Hadley,
Thanks for pointing me to some good articles. Unfortunately, I have already
read Holger's and my main concern is computational efficiency. The buzzword
on this list regarding efficient code is "vectorization". I am, frankly,
surprised that there is a way to vectorize analysis of complex mo
Hi Mark,
If efficiency is a concern you might want to read "Computing Thousands
of Test Statistics Simultaneously in R" by Holger Schwender and Tina
Müller, http://stat-computing.org/newsletter/issues/scgn-18-1.pdf.
If you just want to do it, see the examples in
http://had.co.nz/plyr/plyr-intro-0
Mark Kimpel wrote:
>
> Is it possible to vectorize anova over the output of a vectorized lm?
>
library(nlme)
fm1 <- lmList(distance ~ age | Subject, Orthodont)
lapply(fm1,anova)
Dieter
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Is it possible to vectorize anova over the output of a vectorized lm? I
have a gene expression matrix with each row being a gene and columns for
samples. There are several factors with interactions. I can get p values by
looping over the matrix with lm and anova, but I would like to make this as
c
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