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getting faster results
2 messages · Elizabeth Lawson, Bert Gunter
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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