[R-sig-ME] zero inflated and spatial autocorrelation
alexandre.villers at cebc.cnrs.fr
Wed Sep 23 16:06:52 CEST 2009
(sorry if the message was double posted...)
I currently try to estimate the relative contribution of habitat quality
and a proxy of conspecific attraction for a bird species (3 years of
data: 2000, 2004 and 2008) with a model of the form
Abundance (year t) ~ Abundance (year t-1) + Habitat_quality + Epsi
I would like being able to compare what happened between 2000-2004 to
and would need some advices.
1/ that the distribution of abundance (integer values) is zero inflated,
with 80% of my grid cells "tagged" with 0
2/ I need to account for spatial autocorrelation (which is detectable
below 10 km, my grid being 3 x 3 km in order to account for between
years short dispersal).
I lack some skills in statistics to fully handle this on my own (even if
I try to make up for lost time)
Shall I run straight ahead with a gamm model which is the only one, to
my knowledge, that can account for both the spatial autocorrelation
structure (with for example correlation=corSpher(form=~(X+Y))) and the
zero inflated distribution (with family= negbin) ?
Or is there a way to relax some constraints on the distribution in order
to handle overdispersion (induced by the ZI distribution) and thus trust
the run of a glmmPQL with quasipoisson ?
>From what I read, glmm and gamm are at the edge of statistics and need
to be examined cautiously... so if I can avoid inserting irrelevant
information in it...
Thanks for any help or link
Tiebreaker: my observation window has an irregular shape, meaning that
cells at the edge are truncated. If it is the correct solution to manage
this, how do I properly specify weights=... with the area of cells as
Do I need to transform the value of areas ?
Or would it also be correct to exclude those piece of cells (which are
mainly zeros --> 0 would then represent "only" 68% of observations,
Centre d'Etudes Biologiques de Chizé-CNRS UPR1934
79360 Beauvoir sur Niort
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