[R-sig-ME] Error using MCMCglmm

[Jarrod Hadfield]

Hi,

Is your data frame a tibble? If so, make it a standard data frame and retry.

Cheers,

Jarrod

On 27/12/2021 18:46, Kamal Atmeh wrote:
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>
> Dear list,
>
> I am trying to run bayesian phylogenetic mixed models using MCMCglmm but
> I keep getting the following error:
>
>    " Error in MCMCglmm(ltau ~ x * x2 + lbmM + age + lmean_ndvi + :
>   no slot of name "i" for this object of class "ddiMatrix" "
>
> This is not the first time I use MCMCglmm and it usually works
> flawlessly. I thought that there may be a conflict with the "tidyverse"
> package since some functions of "Matrix" are masked, but I tried to run
> the model without loading the "tidyverse" package and still received the
> same error. I was not able to find answers online and am thus turning to
> this list for answers if you can help please.
>
> I am running the following model:
>
> >>>  prior1 <-list (G = list(G1 = list(V = 1, nu = 0.02)
>                             ,G2 = list(V = 1, nu = 0.02)
>                             ,G3 = list(V = 1, nu = 0.02)
>                             ,G4 = list(V = 1, nu = 0.02)),
>                      R = list(V = 1, nu = 0.02)
>                      )
>
> >>> mod_tau_mc <- MCMCglmm(ltau ~ x * x2+    # x and x2 are categorical
> variables
>                                  lbmM +      # continuous variable
>                                  age +         # categorical
>                                  lmean_ndvi +         # continuous
>                                  lrange_ndvi +         # continuous
>                                  lnb.loc +         # continuous
>                                  lduration         # continuous
>                        , random =
> ~sp_phylo+species2+phylo_pop+phylo_pop_id
>                        , ginverse = list(sp_phylo = inv.phylo$Ainv)
>     # include a custom matrix for argument sp_phylo
>                        , family = "gaussian"
>                        , prior = prior1
>                        , data = dt
>                        , nitt = 22e+03         # number of iteration
> after burnin
>                        , burnin = 2000         # number of iteration
> before beginning sample
>                        , thin = 100         # nb of iteration between
> sample
>                        , pr = TRUE)         #save random posterior
> distribution
>
> I would greatly appreciate your help and happy to provide further
> information if needed!
>
> Thank you in advance!
>
> Kamal
>
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