?? Hello all,
?? I have managed to pretty much understand the MCMCglmm function,
at least to the point of being able to write a model with just a
single response categorical variable and run it. It can be done
without any need to specify any priors. However, when I try to run a
more complicated model with a bivariate response, the problems start.
?? This is the model I am trying to run and the error message I get:
testmodel1<-MCMCglmm(cbind(natapshort,nataplong)~gender+age+religion+sexor+selfattr+partnerattr+gender:age+gender:religion+gender:sexor+gender:selfattr+gender:partnerattr+age:religion+age:sexor+age:selfattr+age:partnerattr+religion:sexor+religion:selfattr+religion:partnerattr+sexor:selfattr+sexor:partnerattr+selfattr:partnerattr,random=NULL,rcov=~us(trait):units,family=c("categorical","categorical"),data=extphen,nitt=10000,singular.ok=TRUE)
????????????????????? MCMC iteration = 0
? Acceptance ratio for latent scores = 0.000154
????????????????????? MCMC iteration = 1000
? Acceptance ratio for latent scores = 0.211168
Error in MCMCglmm(cbind(natapshort, nataplong) ~ gender + age + religion +? :
? Mixed model equations singular: use a (stronger) prior
So I need to define my own priors. As I am still in the testing
stage, I tried some simple ones found in the CourseNotes. Also from
the CourseNotes and other sources, I understand that the term G
refers to random effects, so I should not include it. Then I should
include B and R, am I right? I haven't been able to find very clear
information about what G, B and R refer to.
?? I have tried this:?
?? prior<- list(B= list(B1 = list(V = diag(2), n = 1.002)),R =
list(V = diag(2), n = 1.002))
??? And this is what I get:
??
testmodel1<-MCMCglmm(cbind(natapshort,nataplong)~gender+age+religion+sexor+selfattr+partnerattr+gender:age????? +gender:religion+gender:sexor+gender:selfattr+gender:partnerattr+age:religion+age:sexor+age:selfattr+age:partnerattr????? +religion:sexor+religion:selfattr+religion:partnerattr+sexor:selfattr+sexor:partnerattr+selfattr:partnerattr,random=NULL,?????
rcov=~us(trait):units,family=c("categorical","categorical"),data=extphen,nitt=10000,prior=prior,singular.ok=TRUE)
Error in priorformat(if (NOpriorG) { :
? V is the wrong dimension for some prior$G/prior$R elements
After getting this error, I have tried adding another five B terms
(as I have 6 explanatory variables), but the result is tha same.
If I try just with G and B:
prior<- list(G = list(G1 = list(V = diag(2), n = 1.002)),B = list(V
= diag(2), n = 1.002))
testmodel1<-MCMCglmm(cbind(natapshort,nataplong)~gender+age+religion+sexor+selfattr+partnerattr+gender:age?? +gender:religion+gender:sexor+gender:selfattr+gender:partnerattr+age:religion+age:sexor+age:selfattr+age:partnerattr?? +religion:sexor+religion:selfattr+religion:partnerattr+sexor:selfattr+sexor:partnerattr+selfattr:partnerattr,random=NULL,??
rcov=~us(trait):units,family=c("categorical","categorical"),data=extphen,nitt=10000,prior=prior)
Error in MCMCglmm(cbind(natapshort, nataplong) ~ gender + age + religion +? :
? either both or neither R and G structures need a prior
?? I am getting crazy. Could anybody shed some light on the priors'
issue and help me find some simple ones that can make my model work?
I don't even know where to look any more, I have read plenty of
sources and documents, but I haven't got any clear conclusion yet.
?? Thank you very much.?? Best wishes,?? Iker
?__________________________________________________________________
?? Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations
?? Joseph Banks Laboratories
?? School of Life Sciences
?? University of Lincoln?? Brayford Campus, Lincoln
?? LN6 7DL
?? United Kingdom
?? https://eric.exeter.ac.uk/repository/handle/10036/3381
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