Hello, Thank you all for the comments. Actually, there is a misspelling in my first email and sorry for not explaining properly. I will try below: I collected data in 62 locations along a large spatial scale (> 500 km). And I surely have replication inside each location. First I performed a model selection for identifying the best random structure than the fixed structure. The final best model is as below. m1 = glmmTMB(density ~ wave_exposure + (1|subregion/location), data= mydata, family= nbinom1, ziformula= ~0) The term (1|subregion/location) is the random effect of subregion and location (and location is nested in subregion) When I try to account for spatial correlation a have the following model: m1.spatial = glmmTMB(density ~ wave_exposure + (1|subregion/location) + exp(pos +0|group), data= mydata, family= nbinom1, ziformula= ~0) The term exp(pos +0|group) refers to the spatial correlation. exp = exponential covariance structure; pos = numFactor putting spatial coordinates together; group = a dummy factor (mydata$group <- factor(rep(1, nrow(mydata)))) I already tried to create a jitter for spatial coordinates, since some packages do not work if the distance between two coordinates is zero. I also tried changing the dummy factor to be a repetition from 1 to 62 (since I have 62 locations). Actually, most of times the model not even runs and cracks my R. Well, I guess I will try spaMM. Thanks a lot. Andre. On Fri, 19 Jul 2019 at 09:47, Francois Rousset <
francois.rousset at umontpellier.fr> wrote:
Dear Andr?,
I saw your question on R-sig-ME. I am not sure I fully understand syntax
in "wave_exposure + (1|location) exp(pos + 0|group)" so I hesitate to reply
through R-sig-ME. However, perhaps you should try the spaMM package by
library("spaMM")
m1 <- fitme(density ~ wave_exposure + Matern(1|easting+northing), data=
mydata, family= negbin())
Let me know whether this is useful.
F.
-------- Message transf?r? --------
Sujet : [R-sig-ME] Spatial correlation in glmmTMB
Date : Wed, 17 Jul 2019 18:15:39 +0100
De : Andr? Pardal <andre.pardal.souza at gmail.com>
<andre.pardal.souza at gmail.com>
Pour : r-sig-mixed-models at r-project.org
Hello,
I would like to ask for help on how to account for spatial correlation in
glmmTMB package.
According to the help page (
https://cran.r-project.org/web/packages/glmmTMB/vignettes/covstruct.html),
I need to create a numFactor object grouping coordinates and a dummy
grouping factor.
mydata$pos <- numFactor(mydata$easting, mydata$northing)## spatial
coordinates
mydata$group <- factor(rep(1, nrow(mydata)))## dummy factor
Regarding to the dummy variable, I have 62 locations in my dataframe. The
dummy variable should be 1 for all observations, or go from 1 to 62?
(Actually I have tried both possibilities. First one give me convergence
problems, second one cracks my R).
I have been trying to run the following negative binomial mixed model:
m1 = glmmTMB(density ~ wave_exposure + (1|location) exp(pos + 0|group),
data= mydata, family= nbinom1, ziformula= ~0) ##
I also tried different covariance structures (gau and mat), but no success
so far.
Any ideas or suggestions here?
Thank you in advance!
Andre.
--
Visiting PhD student
School of Ocean Sciences
Bangor University
Menai Bridge, Anglesey, UK
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_______________________________________________R-sig-mixed-models at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
M. Sc. Andr? Luiz Pardal-Souza Doutorando em Evolu??o e Diversidade Centro de Ci?ncias Naturais e Humanas Universidade Federal do ABC (UFABC) Curr?culo Lattes <http://lattes.cnpq.br/6271009643657143> Visiting PhD student School of Ocean Sciences Bangor University Menai Bridge, Anglesey, UK [[alternative HTML version deleted]]