Code from:

Wood, J.L.A, Yates, M.C., and D.J. Fraser. 2016. Are heritability and selection related to population size
in nature? Meta-analysis and conservation implications. Evolutionary Applications.

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library(MCMCglmm)

#######CODE TO TEST THE VARIABLE HYPOTHESIS (EXAMPLE FOR LINEAR GRADIENT DATA)

prior1 = list(R = list(V=1,n=0.002),G = list(G1=list(V = 1,n=0.002),G2 = list(V=1,n=0.002), G3 = list(V=1,n=0.002)))
Lin.Grad = MCMCglmm(grad.lin.value~ln.har.N, random= ~study.ID + pop.ID + idh(sqrt(1/ln.har.N)):units,
mev=LinearGrad.mev, data=LinearGrad, prior=prior1, nitt=6000000, burnin=100000, thin=250, family="gaussian")
summary(Lin.Grad.All)

 
HPDinterval(((Lin.Grad.All$VCV[,3]*(1/log(50))) + Lin.Grad.All$VCV[,5]))
posterior.mode(((Lin.Grad.All$VCV[,3]*(1/log(50))) + Lin.Grad.All$VCV[,5]))

HPDinterval(((Lin.Grad.All$VCV[,3]*(1/log(1000))) + Lin.Grad.All$VCV[,5]))
posterior.mode(((Lin.Grad.All$VCV[,3]*(1/log(1000))) + Lin.Grad.All$VCV[,5]))

HPDinterval(((Lin.Grad.All$VCV[,3]*(1/log(10000))) + Lin.Grad.All$VCV[,5]))
posterior.mode(((Lin.Grad.All$VCV[,3]*(1/log(10000))) + Lin.Grad.All$VCV[,5]))

HPDinterval(((Lin.Grad.All$VCV[,3]*(1/log(100000))) + Lin.Grad.All$VCV[,5]))
posterior.mode(((Lin.Grad.All$VCV[,3]*(1/log(100000))) + Lin.Grad.All$VCV[,5]))