[R-sig-ME] Out of memory with spatial correlation.
Thierry.ONKELINX at inbo.be
Tue Dec 9 13:59:18 CET 2008
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 =
Our nullhypothese is that the average number of recordings does not
depend on the type of vehicule.
The model that fails is:
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).
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
tel. + 32 54/436 185
Thierry.Onkelinx at 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
~ 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
More information about the R-sig-mixed-models