Gabor Grothendieck wrote:
On Wed, Feb 18, 2009 at 7:27 AM, Esmail Bonakdarian <esmail...@gmail.com> wrote:
Gabor Grothendieck wrote:
See ?Rprof for profiling your R code.
If lm is the culprit, rewriting your lm calls using lm.fit might help.
Yes, based on my informal benchmarking, lm is the main "bottleneck", the
rest
of the code consists mostly of vector manipulations and control structures.
I am not familiar with lm.fit, I'll definitely look it up. I hope it's
similar
enough to make it easy to substitute one for the other.
Thanks for the suggestion, much appreciated. (My runs now take sometimes
several hours, it would be great to cut that time down by any amount :-)
Yes, the speedup can be significant. e.g. here we cut the time down to
40% of the lm time by using lm.fit and we can get down to nearly 10% if
we go even lower level:
Wow those numbers look impressive, that would be a nice speedup to have.
I took a look at the manual and found the following at the top of
the description for lm.fit:
"These are the basic computing engines called by lm used to fit linear
models. These should usually not be used directly unless by experienced
users. "
I am certainly not an experienced user - so I wonder how different it
would be to use lm.fit instead of lm.
Right now I cobble together an equation and then call lm with it and the
datafile.
I.e.,
LM.1 = lm(as.formula(eqn), data=datafile)
s=summary(LM.1)
I then extract some information from the summary stats.
I'm not really quite sure what to make of the parameter list in lm.fit
I will look on-line and see if I can find an example showing the use of
this - thanks for pointing me in that direction.
Esmail
system.time(replicate(1000, lm(DAX ~.-1, EuStockMarkets)))
user system elapsed
26.85 0.07 27.35
system.time(replicate(1000, lm.fit(EuStockMarkets[,-1], EuStockMarkets[,1])))
user system elapsed
10.76 0.00 10.78
system.time(replicate(1000, qr.coef(qr(EuStockMarkets[,-1]),
EuStockMarkets[,1])))
user system elapsed
3.33 0.00 3.34
lm(DAX ~.-1, EuStockMarkets)
Call:
lm(formula = DAX ~ . - 1, data = EuStockMarkets)
Coefficients:
SMI CAC FTSE
0.55156 0.45062 -0.09392
# They call give the same coefficients:
lm.fit(EuStockMarkets[,-1], EuStockMarkets[,1])$coef
SMI CAC FTSE
0.55156141 0.45062183 -0.09391815
qr.coef(qr(EuStockMarkets[,-1]), EuStockMarkets[,1])
SMI CAC FTSE
0.55156141 0.45062183 -0.09391815
______________________________________________
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.
