On 3Feb 2020, at 10:03, Willem (Wim) Kaijser
<willem.kaijser at uni-due.de> wrote:
Hello, It was suggested to me to place my question in this
mailing-list. I have some problems and lack of knowledge
constructing a GLMM with the glmmTMB package (version 0.2.03).
Therefore, I am sorry If the explanation is not as sufficient as it
should be, and want to thank you in advance for your time.
I try to include both fixed plus random effects and correction for
serial correlation in a GLMM with a Gamma distribution (link =
"inverse"). However, I get several warnings and the processing time
is long, so I prematurely stopped the permutations (see the code
below). If the Gamma distribution, with ?log? link, is used in
the model containing only the fixed and random effects; these
warnings do not occur. Including this with the model correcting for
serial correlation it does return a warning, but I can extract the
residuals (AIC and BIC are returned as NA though). This seems like
the following issue: https://github.com/glmmTMB/glmmTMB/issues/329
[1]. However, this seems to be resolved. What might be the issue
here (is it my coding)?
############################################################
#Code with only the fixed and random effects with warnings:#
############################################################
mod1 <- glmTMB(Chla ~ pCO2 + (1|River/ID), family = ?Gamma?,
data = df)
There were 19 warnings (use warnings() to see them)
Timing stopped at: 33.7 0.08 34.19
Warning messages:
1: In nlminb(start = par, objective = fn, gradient = gr, ... :
NA/NaN function evaluation
This coding looks correct, but can you say something about River and
ID in the design. Are the labels for the levels of one reused in the
levels of the other?
The default in glmmTMB is to use an inverse link with the Gamma family
because that?s what glm() does in base R, but I don?t actually
know why. Since the mean has to be positive, I would guess that a log
link is a good thing to try, but maybe someone else can explain why
inverse is the default.
#######################################################################################
#Code with both the fixed, random and correction for serial
correlation with warnings:#
#######################################################################################
mod2 <- glmTMB(Chla ~ pCO2 + (1|River/ID) + ar1(1|Month), family =
?Gamma?, data = df)
This coding is not correct. Check out the issue you linked to.
https://github.com/glmmTMB/glmmTMB/issues/329 [1]
If Month is an integer, then you could use ar1(Month+0 | X) where X is
probably ID, or possibly River depending on the design. This also
depends on if the experiment ran for more than 12 months, in which
case, you do not want to repeat 1:12 in the second year if it is based
on calendar months. In ar1(Time +0 | X), you need Time to continue
counting even if Month repeats according to the calendar in the data.
Cheers,
Mollie
There were 20 warnings (use warnings() to see them)
Timing stopped at: 24.71 0.08 25.49
Warning messages:
1: In FUN(X[[i]], ...) : AR1 not meaningful with intercept
2: In nlminb(start = par, objective = fn, gradient = gr, ... :
NA/NaN function evaluation
Best regards,
--
Willem (Wim) Kaijser
Fakult?t f?r Biologie
Aquatische ?kologie
Universit?tsstr. 5
D-45141 Essen
Room: S05T03B02
Tel: +49.201.183.3113