[R] quantile regression: out of memory error

[Prew, Paul]

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
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