[R] quantile regression: out of memory error

[Prew, Paul]

Thank you, Roger, that was my problem.  Specifying tau = 1:19/20 worked fine.  Regards, Paul

Paul Prew  |  Statistician
651-795-5942   |   fax 651-204-7504 
Ecolab Research Center  | Mail Stop ESC-F4412-A 
655 Lone Oak Drive  |  Eagan, MN 55121-1560 


-----Original Message-----
From: Roger Koenker [mailto:rkoenker at uiuc.edu] 
Sent: Monday, July 11, 2011 12:48 PM
To: Prew, Paul
Cc: r-help at r-project.org help
Subject: Re: [R] quantile regression: out of memory error

Paul,

Yours is NOT a large problem, but it becomes a large problem when you ask for ALL the distinct
QR solutions by specifying tau = -1.  You probably don't want to see all these solutions, I suspect
that only tau = 1:19/20 or so would suffice.  Try this, and see how it goes.

Roger

url:    www.econ.uiuc.edu/~roger            Roger Koenker
email    rkoenker at uiuc.edu            Department of Economics
vox:     217-333-4558                University of Illinois
fax:       217-244-6678                Urbana, IL 61801

On Jul 11, 2011, at 12:39 PM, Prew, Paul wrote:

> Hello,  I’m wondering if anyone can offer advice on the out-of-memory error I’m getting. I’m using R2.12.2 on Windows XP, Platform: i386-pc-mingw32/i386 (32-bit).
> 
> I am using the quantreg package,  trying to perform a quantile regression on a dataframe that has 11,254 rows and 5 columns.
> 
>> object.size(subsetAudit.dat)
> 450832 bytes
> 
>> str(subsetAudit.dat)
> 'data.frame':   11253 obs. of  5 variables:
> $ Satisfaction     : num  0.64 0.87 0.78 0.75 0.83 0.75 0.74 0.8 0.89 0.78 ...
> $ Return           : num  0.84 0.92 0.91 0.89 0.95 0.81 0.9 0.87 0.95 0.88 ...
> $ Recommend        : num  0.53 0.64 0.58 0.58 0.62 0.6 0.56 0.7 0.64 0.65 ...
> $ Cust.Clean       : num  0.75 0.85 0.72 0.72 0.81 0.79 0.79 0.8 0.78 0.75 ...
> $ CleanScore.Cycle1: num  96.7 83.3 93.3 86.7 96.7 96.7 90 80 81.7 86.7 ...
> 
> rq(subsetAudit.dat$Satisfaction ~ subsetAudit.dat$CleanScore.Cycle1, tau = -1)
> 
> ERROR:  cannot allocate vector of size 2.8 Gb
> 
> I don’t know much about computers – software, hardware, algorithms – but does this mean that the quantreg  package is creating some massive intermediate vector as it performs the rq function?   Quantile regression is something I’m just starting to explore, but believe it involves ordering data prior to the regression, which could be a huge job when using 11,000 records.   Does bigmemory have functionality to help me with this?
> 
> Thank you,
> Paul
> 
> 
> 
> 
> 
> 
> Paul Prew   ▪  Statistician
> 651-795-5942   ▪   fax 651-204-7504
> Ecolab Research Center   ▪  Mail Stop ESC-F4412-A
> 655 Lone Oak Drive   ▪   Eagan, MN 55121-1560
> 
> 
> 
> 
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