[ADMB Users] separable runs slower in Catch-at-Age model
thg at hafro.is
Fri Nov 20 05:37:08 PST 2009
there are files caresnr.tpl and .dat
where catch at age data (7x41) is simulated
with errors in catch, recruitment and stock (i.e. M?).
Random walk in F and Selection.
Exactly the same model is fitted
with all variables initialised to their true value.
Random effects are N(age,year), F(year) and 50% Selection_age(year)
When I change all the SEPARABLE_FUNCTIONS to just FUNCTION
the run-time is slightly shorter.
The run command is in file xrun on the directory.
>uname -a is:
Linux hafskip 220.127.116.11-96.fc11.x86_64 #1 SMP Wed Nov 4 00:02:04 EST 2009
x86_64 x86_64 x86_64 GNU/Linux
Another conundrum which may not be specific to admb,
since there may have been a similar experience with a Kalman filter program.
the same model is fitted but only the Initial stock and N at first age
is estimated as RE.
The stock is then forward calculated
(not a separable model but runs ten times faster since there are much
fewer estimated param).
I also tried estimating the final stock and N at the highest age
and back calculating.
That is in line with the old style of VPA by adding catches.
I thought this would be computationally faster.
The backward version bwfsr.tpl loops printing Max gradient=0 ?
If the Ny0 is estimated not as RE the results are similar to the forward
so I am inclined to believe this is not a programing error.
A simpler version bwfs.tpl runs but slower than fwfs.tpl but results are
I had in mind to compare to a version in which the stock would be
calculated backwards by adding catches but could not be done.
A versions of the separable program above caresnr.tpl where the stock
uses the catch rather than F is slower or runs into problems with Hessian?
Thanks in advance
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