[R] getting faster results
Berton Gunter
gunter.berton at gene.com
Wed Dec 14 19:00:42 CET 2005
What is almost certainly critical here are the algorithms you use (to do the
integrations in the Bayesian models) and perhaps a fast BLAS.
-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
"The business of the statistician is to catalyze the scientific learning
process." - George E. P. Box
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
> Elizabeth Lawson
> Sent: Wednesday, December 14, 2005 9:53 AM
> To: jim holtman
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] getting faster results
>
> I am running algorithms for Bayesian hierarchical models with
> 20 or more variables or writing alogrithms that solve for
> partially linear models using wavlelet estimation. Soemtimes
> just creating the predicted vaules from the Bayesian analysis
> takes over a day to run!
> I am just wondering if R runs faster on any particular
> systems or if it is about the same regardless.
>
> jim holtman <jholtman at gmail.com> wrote:
> Need to know what you are trying to do with the data.
> Depending on what you want to do and how you do it will
> determine the speed. I can take a dataframe with 1,000,000
> rows of transaction data and compute the average and plot a
> histogram of the response time in less that a couple of
> seconds. Is that fast enough?
>
> On 12/13/05, Elizabeth Lawson <lizzylaws at yahoo.com> wrote: Hey,
>
> Can anyone answer this question. I am working with really
> large datasets and most of the programs I have been running
> take quite some time.
>
> I heard that R may be faster in Unix. I sthis true and if so
> can anyone reccomend which system and requirements may allow
> things to go faster for?
>
> Thanks!!
>
> Elizabeth Lawson
>
>
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>
> --
> Jim Holtman
> Cincinnati, OH
> +1 513 247 0281
>
> What the problem you are trying to solve?
>
>
>
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