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Long vectors not supported #3
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Interesting. I have never tried so many parameters with this. Are you
using parallelization and the mcapply function? It looks like there could
be a problem with mcapply calling stan with large models.
Check this post: stan-dev/rstan#378
The Laplace and horseshoe models will nearly double the number of
parameters over the normal model, so that could explain the difference.
You may have to run chains in sequence.
I have not set up the model code yet to handle multiple observations per
grid cell. Otherwise you could try reducing the dimension of your grid. I
will look into making that fix.
…On Tue, May 2, 2017 at 10:32 AM, George ***@***.***> wrote:
I ran the model against a long vector (15,100). Running the model with a
normal prior runs OK but running the same with a Laplace prior gives an
error on completion.
Error in sendMaster(try(eval(expr, env), silent = TRUE)) :
long vectors not supported yet: fork.c:376
Error in FUN(X[[i]], ...) :
trying to get slot "mode" from an object (class "try-error") that is not an S4 object
In addition: Warning message:
In parallel::mclapply(1:chains, FUN = callFun, mc.preschedule = FALSE, :
4 function calls resulted in an error
The error could be R specific but I am not sure if it has to do with the
class of model fit object. What are your thoughts?
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Yes, it does look like variant of stan-dev/rstan#378 issue. I will ran with fewer iterations and chains and assess the convergence. Glad you will look into the issue. Many thanks. |
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I ran the model against a long vector (15,100). Running the model with a normal prior runs OK but running the same with a Laplace prior gives an error on completion.
The error could be R specific but I am not sure if it has to do with the class of model fit object. What are your thoughts?
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