Hi INLA users,
In my computation when I fix the hyperparameters precision (log precision), INLA takes a long time to converge. Can you tell me what can be a possible reason? I write a snippet of code.
PS: I have a 15 random effect spatially varying coefficients. As INLA takes a long time to converge if I do not fix i am putting some initial value. Smaller precision sometime helps. But with an example of big data, without fixing the hyperparameters I got the initial guess.
f(as.numeric(spatial_ID_13),value_r1__value_u1,
constr=FALSE,
model = "besag",scale.model=TRUE,
graph = graph_adjacency_2,
hyper=list(theta = list(prior = "loggamma",
param=c(1,.0003),
initial=log(5.0),
fixed=TRUE,
scale.model=TRUE)
)
)
The other alignment is
```
family = "poisson" ,
data = data.frame(x_matrix_2) ,
control.predictor = list(compute = TRUE),
control.compute = list(openmp.strategy = "huge",
dic = TRUE,config = TRUE,
save.memory = TRUE),
control.inla = list(
#diagonal = .01,
strategy="gaussian",
int.strategy = "eb"
),
#verbose=TRUE,
control.mode=list(restart=T)
```