Out of memory with spatial correlation.
Dear Dimitris, Restricting the correlation to the Group (and to Occasion nested in Group) did not solve my problem. I even tried to subset the data to one groep with no avail. 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 -----Oorspronkelijk bericht----- Van: Dimitris Rizopoulos [mailto:d.rizopoulos at erasmusmc.nl] Verzonden: dinsdag 9 december 2008 15:14 Aan: ONKELINX, Thierry CC: R-sig-mixed-models at r-project.org Onderwerp: Re: [R-sig-ME] Out of memory with spatial correlation. Is it reasonable to assume that spatial correlation only exists within groups, e.g., lme(log(Pulses + 1) ~ Transport + Occasion, random = ~ 1 | Group, correlation = corExp(form = ~ X + Y | Group)) Best, Dimitris
ONKELINX, Thierry wrote:
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 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.
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
Dimitris Rizopoulos Assistant Professor Department of Biostatistics Erasmus Medical Center Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands Tel: +31/(0)10/7043478 Fax: +31/(0)10/7043014 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.