[R-sig-ME] Predicting values from MCMCglmm model with statistical weight in mev argument

[Jarrod Hadfield]

Hi Kamal,

Can you post your sessionInfo()?

As a work around, use this model

model <- MCMCglmm(lD ~ tactic*period*seasonality+complique_KF+lbody+lintdur+lnb.loc+lduration
                                     , random = ~sp_phylo+species2+phylo_pop+phylo_popY+phylo_pop_id + idh(SE):units,
                                     , family = "gaussian"
                                     , ginverse = list(sp_phylo = inv.phylo$Ainv) # include a custom matrix for argument phylo
                                     , prior = prior1
                                     , data = Data
                                     , nitt = 22e+04
                                     , burnin = 20000
                                     , thin = 100
                                     , pr=TRUE)

BUT make sure to fix the prior variance associated with the final random effect term (idh(SE):units) to one. Its identical to the model you've fitted, but the predict function should work.

Cheers,

Jarrod

On 15/02/2020 22:57, Kamal Atmeh wrote:
model <- MCMCglmm(lD ~ tactic*period*seasonality+complique_KF+lbody+lintdur+lnb.loc+lduration
                                     , random = ~sp_phylo+species2+phylo_pop+phylo_popY+phylo_pop_id
                                     , family = "gaussian"
                                     , mev = SE^2 # error variance associated to each data point
                                     , ginverse = list(sp_phylo = inv.phylo$Ainv) # include a custom matrix for argument phylo
                                     , prior = prior1
                                     , data = Data
                                     , nitt = 22e+04
                                     , burnin = 20000
                                     , thin = 100
                                     , pr=TRUE)
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