[R] Dynamic Programming in R

Arne.Muller@sanofi-aventis.com Arne.Muller at sanofi-aventis.com
Fri Jan 20 12:19:21 CET 2006


I've implemented dynamic programming for aligning spectral data (usually 100 to 200 peaks in one spectrum, but some spectra contain > 5k peaks) entirely in R. As François Pinard pointed out, the memory usage should be proportional to the n x n dynamic programming matrix, and I've not yet had any problems on my machine (R2.2.0 win2k, 1GB mem, 2GHz Intel PV), CPU seems to be the more problematic issue. 

I guess it all depends on how much data you have. You could split the dynamic programming matrix into chunks and calculate them in parallel on different machines (but the implementatino of finding the optiomal trace will probably get a bit difficult).

	kind regards,


-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Arnab mukherji
Sent: Thursday, January 19, 2006 22:55
To: r-help at stat.math.ethz.ch
Subject: [R] Dynamic Programming in R

Hi R users,

I am looking to numerically solve a dynamic program in the R environment. I was wondering if there were people out there who had expereinced success at using R for such applications. I'd rather continue in R than learn Mathlab.

A concern that has been cited that may discourage R use for solving dynamic programs is its memory handling abilities.  A senior researcher had a lot of trouble with R becuase on any given run it would eat up all the computers memory and need to start using the hard disk. Yet, the memory needed was not substantial - saving the worksapce, exiting and recalling would noticebly start of tthe progam at a much lower memory use, level and a quick deteroration in a few thousand iterations.

Is this a problem other people have come across? Perhaps, its a problem already fixed, since the researcher was working on this in 2002 (he claimed he had tried it on windows, mac, and unix versions to check). 



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