"length of 'dimnames' [1] not equal to array extent" error when apply inla.posterior.sample()

[lisa C]

Dear all,

I have applied the following inla model. In my model, I have 11 covariates and a GMRF spatial random field. I also included a linear combination predictor (mycomb).

M2 <- inla(f2, 

           family = "gaussian",

           lincomb =mycomb,

           data = inla.stack.data(mystack),

           control.compute = list(dic = TRUE, waic = TRUE, 

                                  openmp.strategy="huge",

                                  config = TRUE),

           control.predictor = list(

             A = inla.stack.A(mystack)),

           control.inla = list (lincomb.derived.only = FALSE,

                                strategy = "gaussian", int.strategy = "eb"),

           verbose=TRUE

)

Now I would like to sample from the joint posterior distribution:

mysample <- inla.posterior.sample(n=100, result=M2)

However, I have got the following error:

Error in dimnames(x) <- dn : 

  length of 'dimnames' [1] not equal to array extent

Can someone help me with where i should check the error is? 

Thanks

Chun

[Helpdesk]

can you send me code so I can rerun this here?

thx
H

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Håvard Rue
Helpdesk
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[Helpdesk]

On Wed, 2018-09-12 at 01:56 -0700, lisa C wrote:
>

> control.inla = list (lincomb.derived.only = FALSE,

set this to TRUE, or just remove that argument (TRUE is default).
you do not need this, and its a feature that is not recommended for use
any more.

[lisa C]

Thanks! it works after setting (lincomb.derived.only=TRUE.