## Load packages install.packages('MCMCglmm', repos='http://cran.wustl.edu/') install.packages('MASS', repos='http://cran.wustl.edu/') install.packages('orthopolynom', repos='http://cran.wustl.edu/') library(MCMCglmm) library(MASS) library(orthopolynom) ## LOAD ONE PHYLOGENY mytree1 <- read.tree('Tree1.txt') plot(mytree1) G<-vcv(mytree1) ## GENERATE DATA WITH PHYLOGENETIC EFFECTS + REPETITION rep = 20 nspecies = nrow(G) re <- mvrnorm(1, c(0, 0, 0, 0, 0), G) resid <- rnorm(rep*nspecies, 0, .5) mymev <- rnorm(rep*nspecies, 0, .1) y<- array(0, dim=c(rep*nspecies)) for(i in 1:nspecies){ for(j in 1:rep){ n=rep*(i-1) + j y[n] = re[i] + resid[n] }} x<- c(rep('A', rep), rep("B",rep), rep("C", rep), rep("D", rep), rep("E", rep)) ## TRY TO GET MCMCglmm TO ANALYZE THE DATA mydata <- data.frame(y=y,animal=x) ginv_G <- inverseA(mytree1) prior<-list(R=list(V=1, nu=0.002), G=list(G1=list(V=1, nu=0.002))) out <- MCMCglmm(y~1, random=~animal, data=mydata, prior=prior, pedigree=mytree1, mev=mymev, verbose=TRUE) summary(out)