My question might be rather basic, theoretical. I am running spatial and spatial-temporal bayesian models in INLA. I have areal data and a continuous response variable with spatial and temporal dependencies. I've got error messages during model runs, sometimes they point to optimisation that failed or to bad initial parameters. Anyway, I've got a comment from INLA developers that my problem is in the "singularity of the model", that they way I construct the model, it easily becomes singular.
My question is banal: what does it mean that the model is singular? I understand that matrices can be singular, and that's a problem in modelling but in this case, it means something else. Would you please give some hints or links to resources with explanations on the matter?
For particularly interested and familiar with INLA syntax, here an example of my model:
form7 <- total_catch_ton ~ sea_area + percent_wforce +distance + popgrowth + aqua_prod_ton +
f(ID,
model = "bym2",
hyper=HyperBYM2,
graph = seafood.sel.path,
adjust.for.con.comp = TRUE,
scale.model = TRUE,
constr = TRUE) +
f(year1,
model="rw2") +
f(year2,
model = "iid") +
f(id.year, model = "iid")
M7 <-inla(formula = form7,
family = "tweedie", scale = ,
data=seafood,
verbose=T,safe=T,
control.fixed=list(prec=1,prec.intercept=1),
control.compute = list(dic = TRUE,
waic = TRUE))
```