[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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