Hi Vasco,
With only 20 observations, you probably need to simplify your model. The
best you can really hope for is to estimate 2 parameters. First try
dropping (1|Plot:Grazing).
The Tweedie distribution is also available now. Try family=tweedie(link =
"log").
cheers,
Mollie
On 17Feb 2018, at 5:54, Vasco Silva <silvadavasco at gmail.com> wrote:
Hi,
I am trying to fit a GLMM on biomass for each individual species using
glmmTMB but I got the following warning messages. I start to model the
zeros in a binomial model and the non-zeros in Gamma.
str(biomass)
'data.frame': 20 obs. of 15 variables:
$ Plot : Factor w/ 10 levels "P1","P10","P2",..: 1 3 4 5 6 7 8 9
10 2 ...
$ Grazing : Factor w/ 2 levels "Fenced","Unfenced": 1 1 1 1 1 1 1 1
1 1 ...
$ sp1 : num 247.61 10.9 0 24.92 2.14 ...
$ sp2 : num 244 0 0 2907 0 ...
$ sp3 : num 2147 2410 1030 1227 368 ...
$ sp3 : num 0 0 0 0 0 ...
##
m0<-glmmTMB(sp2.positive ~ Grazing+(1|Plot)+(1|Plot:Grazing),
data=biomass,family=binomial(link="logit"))
$cond
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.386333 0.9845106 -1.408144 0.1590885
GrazingUnfenced 2.233656 1.4343891 1.557218 0.1194188
$zi
NULL
$disp
NULL
##
m1<-glmmTMB(sp2~Grazing+(1|Plot)+(1|Plot:Grazing),data=bioma
ss[biomass$sp2>0,],
family=Gamma(link="log"),control=glmmTMBControl(optCtrl=
list(iter.max=1e3,eval.max=1e3)))
#Warning messages:1: In fitTMB(TMBStruc) :
Model convergence problem; extreme or very small eigen values
detected. See vignette('troubleshooting')2: In fitTMB(TMBStruc) :
Model convergence problem; false convergence (8). See
vignette('troubleshooting')
I check the vignette (troubleshooting) of the package but I can?t fix the
problem. Should I (re)scale the data? I saw that Tweedie is not (yet)
implemented in glmmTMB (
https://cran.r-project.org/web/packages/glmmTMB/vignettes/glmmTMB.pdf).
Any
alternative for modeling zero-inflated continuous data?
I would greatly appreciate it if someone could help me.
Cheers.
Vasco Silva
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