[R-sig-ME] Priors for us(trait):units structure in MCMCglmm model. Error message - help needed.

Tricia Markle markl033 at umn.edu
Mon Jan 26 07:05:20 CET 2015


I am hoping that someone could provide some thoughts on an appropriate
prior set-up for my model which uses a “us(trait):units” structure in an
MCMCglmm model with repeat measures and a phylogeny component.

I am assuming that I need to use uninformative proper priors with a set-up
something along the lines of:

prior<-list(G=list(G1=list(V=diag(#), nu=#)), R=list(V=diag(#), n=#))

I have spent a considerable amount of time working on this (looking at help
guides, posted examples etc.) and regardless of what numbers I try, I
continue to get the following error message:

Error in priorformat(if (NOpriorG) { :

  V is the wrong dimension for some prior$G/prior$R elements

Data Details: I have 308 individual salamanders, each acclimated at 3
different temperatures (6,14,22C). Then for each acclimation temperature
metabolic rate is measured at 3 test temperatures (5, 15, 25C) (so total of
9 trials per individual).

I am attempting to compare slopes of the test temperatures between
acclimation temperatures. There are 18 species, but my main question is
whether large ranging species have greater differences in slope between
acclimation temps than narrow ranging species (species are divided into
those with small (1) versus large (2) ranges).

Here is the rest of my code:

dataset<-read.csv(file="RespData.csv", head=TRUE)



#Phylogeny Component


species<-c("D._carolinensis", "D._fuscus", "D._imitator", "D._ochrophaeus",
"D._ocoee", "D._orestes",  "D._monticola_A",  "D._santeetlah",
"P_cinereus", "P_cylindraceus", "P_glutinosus", "P_hubrichti",
"P_montanus", "P_punctatus", "P_richmondi", "P_teyahalee", "P_virginia",

tree$tip.label)])# Prune tree to just include species of interest

sptree<-makeNodeLabel(pruned.tree, method="number", prefix="node") #rename
nodes to be unique

treeAinv<-inverseA(sptree, nodes="TIPS")$Ainv


#note, I could alternatively use random=~us(1+Temp):species, but results
are likely harder to interpret

prior<-list(G=list(G1=list(V=diag(#), nu=#)), R=list(V=diag(#), n=#))

random=random, data=dataset, family="gaussian",
ginverse=list(species=treeAinv), prior=prior, nitt=300000, burnin=25000,
thin = 1000, verbose=FALSE)

Thank you kindly for your help.


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