[R-sig-ME] Out of memory with spatial correlation.

[Doran, Harold]

Refer to sections 5.1 et seq for the linear transformations 

> -----Original Message-----
> From: ONKELINX, Thierry [mailto:Thierry.ONKELINX at inbo.be] 
> Sent: Thursday, December 11, 2008 8:10 AM
> To: Doran, Harold; R-sig-mixed-models at r-project.org
> Subject: RE: [R-sig-ME] Out of memory with spatial correlation.
> 
> Dear Harold,
> 
> Could you point me to the relevant section in Pinheiro and 
> Bates? I have been looking for it, but can't find it.
> 
> Thanks,
> 
> Thierry
> 
> 
> --------------------------------------------------------------
> ----------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute 
> for Nature and Forest Cel biometrie, methodologie en 
> kwaliteitszorg / Section biometrics, methodology and quality 
> assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 
> 54/436 185 Thierry.Onkelinx at inbo.be www.inbo.be 
> 
> To call in the statistician after the experiment is done may 
> be no more than asking him to perform a post-mortem 
> examination: he may be able to say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
> 
> The plural of anecdote is not data.
> ~ Roger Brinner
> 
> The combination of some data and an aching desire for an 
> answer does not ensure that a reasonable answer can be 
> extracted from a given body of data.
> ~ John Tukey
> 
> -----Oorspronkelijk bericht-----
> Van: Doran, Harold [mailto:HDoran at air.org]
> Verzonden: dinsdag 9 december 2008 15:02
> Aan: ONKELINX, Thierry; R-sig-mixed-models at r-project.org
> Onderwerp: RE: [R-sig-ME] Out of memory with spatial correlation.
> 
> Thierry
> 
> One option is to switch to lmer rather than lme. Of course, 
> with lmer you don't have the same options for correlation 
> structures. So, what you might consider is to "pre-whiten" 
> your data using the methods outlined in Pinhiero and Bates 
> and then run the model using lmer.
> 
> In fact, that is what lme does. It "pre-whitens" the data and 
> then runs the model under normal assumptions. The only 
> difference here is that you would need to pre-whiten manually. 
> 
> > -----Original Message-----
> > From: r-sig-mixed-models-bounces at r-project.org
> > [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of 
> > ONKELINX, Thierry
> > Sent: Tuesday, December 09, 2008 7:59 AM
> > To: R-sig-mixed-models at r-project.org
> > Subject: [R-sig-ME] Out of memory with spatial correlation.
> > 
> > Dear all,
> > 
> > My model runs fine with just the fixed and random effects. 
> > But when I add a spatial correlation structure it runs out 
> of memory 
> > (Error: cannot allocate vector of size 185.6 Mb). The 
> problem is that 
> > the data is clearly spatially correlated. I have tried the simplify 
> > the fixed effects and the random effects with no avail. So 
> the problem 
> > is probably in the correlation structure (see code below). Any 
> > suggestion on how to incorporate the spatial autocorrelation?
> > 
> > A description of the design.
> > 
> > We are testing a methodology to monitor bats. Basically volunteers 
> > ride along a predefined route by car (30 km/h) or by bike 
> (15 km/h). 
> > They record the echolocation sounds of the bats at fixed intervals. 
> > There position is tracked by GPS so we know were each recording was 
> > made. An expert counts the number of pulses in each recording.
> > We predefined 10 routes, 5 for the cars and 5 for the bikes. 
> > Each car route overlaps with one bike route. So we have 5 groups of 
> > routes.
> > Within each group we have an longer car route that overlaps with a 
> > shorter bike route. There is no overlap between groups. All routes 
> > were driven three times, all vehicules started their route 
> > simultanious.
> > We have about 400 recordings per route of 10 routes at 3 
> occasions = 
> > 12000 rows.
> > 
> > Our nullhypothese is that the average number of recordings does not 
> > depend on the type of vehicule.
> > 
> > The model that fails is:
> > library(nlme)
> > lme(log(Pulses + 1) ~ Transport + Occasion, random = ~ 1| Group, 
> > correlation = corExp(form = ~ X + Y))
> > 
> > The model works if I omit the correlation structure:
> > lme(log(Pulses + 1) ~ Transport + Occasion, random = ~ 1| Group)
> > 
> > I'm using R 2.8.0 with nlme 3.1-89 on WinXP with 2GB RAM. 
> > --mem-size is set at the maximum (2047 MB).
> > 
> > Regards,
> > 
> > Thierry
> > 
> > 
> > --------------------------------------------------------------
> > ----------
> > ----
> > ir. Thierry Onkelinx
> > Instituut voor natuur- en bosonderzoek / Research Institute 
> for Nature 
> > and Forest Cel biometrie, methodologie en kwaliteitszorg / Section 
> > biometrics, methodology and quality assurance Gaverstraat 4 9500 
> > Geraardsbergen Belgium tel. + 32
> > 54/436 185 Thierry.Onkelinx at inbo.be www.inbo.be
> > 
> > To call in the statistician after the experiment is done may be no 
> > more than asking him to perform a post-mortem
> > examination: he may be able to say what the experiment died of.
> > ~ Sir Ronald Aylmer Fisher
> > 
> > The plural of anecdote is not data.
> > ~ Roger Brinner
> > 
> > The combination of some data and an aching desire for an 
> answer does 
> > not ensure that a reasonable answer can be extracted from a 
> given body 
> > of data.
> > ~ John Tukey
> > 
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> > INBO, as long as the message is not confirmed by a duly signed 
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> > 
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> > 
> 
> Dit bericht en eventuele bijlagen geven enkel de visie van de 
> schrijver weer en binden het INBO onder geen enkel beding, 
> zolang dit bericht niet bevestigd is door een geldig 
> ondertekend document. The views expressed in  this message 
> and any annex are purely those of the writer and may not be 
> regarded as stating an official position of INBO, as long as 
> the message is not confirmed by a duly signed document.
>