You are probably running out of memory address space. Can you
1) Try this in 1.9.0 beta which gives a more informative error message,
and
2) Use traceback() and the debugging tools to locate the error more
exactly.
3) Consider using the options to loess to reduce the load. Loess is not
designed for smoothing a 2D grid and you appear only to want the fitted
values at your grid. If so, try the fitted() extractor function.
(Or the residual() extractor function if all you want are residuals.)
On Wed, 24 Mar 2004, Thomas Jagoe wrote:
> Hi,
> I have been successfully using the loess function for normalisation of a 2D
> array set.
> We have recently improved the quality criteria for the data and the numbers
> of data points has been reduced to around from around 1000 to 700.
> Previously the following would return the loess normalised values for
> array$logratio but I am now getting an error:
>
> > array <- read.table("A1.txt", header=T,
sep="\t")
> > array$logratio<-array$logs555-array$logs647
> > array$logav<-(array$logs555+array$logs647)/2
> > library(modreg)
> > loess2d<-loess(logratio~x+y,data=array)
> > array$logratio2DLoeNorm <-array$logratio - predict(loess2d, array)
> Error in vector("double", length) : negative length vectors are
not allowed
>
> I am assuming that this is due to a problem fitting the data at some
> locations and I have tried altering span without much success. Can anyone
> please advise ?
>
> With thanks
>
> Thomas
>
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>
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
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