[R-sig-ME] glmmADMB errors
andreu blanco
andreu.blanco at gmail.com
Fri Oct 20 14:08:02 CEST 2017
Thanks Mollie,
In fact, I am following instructions from the Zuur's book Beginner's guide
to zero inflated models and he suggests something similar to what you have
proposed. Hurdle models:
First modelling with a binomial distribution when biomass is present or not
and second, once is present with Gamma see which variables are affecting
the present biomass, plus glueing both models together in a ZAG. However I
am having some further problems since one of my varibles is random and
nested, which I think the model doesn't like that much, although it allows
to use glmer in such cases.
However, using glmmADMB with the gamma family still returns errors:
> Model_ADMB_G<-glmmadmb(Biomass~Protection*Exposure+(1|Protection/Location),data=GLMMADMB_P,
family="gamma")
Error in glmmadmb(Biomass ~ Protection + Exposure + Protection:Exposure +
:
The function maximizer failed (couldn't find parameter file)
Troubleshooting steps include (1) run with 'save.dir' set and inspect
output files; (2) change run parameters: see '?admbControl';(3) re-run with
debug=TRUE for more information on failure mode
Además: Warning message:
comando ejecutado 'C:\WINDOWS\system32\cmd.exe /c glmmadmb -maxfn 500
-maxph 5 -noinit -shess' tiene estatus 1
I hope someone can see what I am doing wrong. Thanks in advance
On 20 October 2017 at 13:51, Mollie Brooks <mollieebrooks at gmail.com> wrote:
> Hi Andreu,
>
> A zero-inflated Poisson distribution is not appropriate because biomass is
> not count data. I would recommend checking what distribution other
> researchers in your field are using. Maybe you want to first model zero vs
> non-zero and then model the non-zero biomasses separately. The log of
> non-zero biomasses could be modeled with a normal distribution. Or on the
> natural scale, they could be Gamma or Tweedie. Or maybe a zero-inflated
> continuous positive distribution (e.g. Gamma or Tweedie) makes sense for
> all of the biomasses. These zero-inflated models could be fit in glmmTMB.
>
> cheers,
> Mollie
>
> On Thu, Oct 19, 2017 at 2:03 PM, andreu blanco <andreu.blanco at gmail.com>
> wrote:
>
>> Dear list members, I am starting with generalized mixed models and I am
>> having some trouble I hope someone could help me with.
>>
>> We are trying to understand the invasiveness of algae inside and outside
>> MPA, to do so our sampling was set with a nested desing:
>>
>> Protected vs nonProtected
>> 4 Locations (protected) vs 4 Locations (nonProtected)
>> Exposed vs Semiexposed at each location
>> 1 transect per sampling point (total 16)
>> 5 quadrants per transect
>>
>> str(dataGLMMADMB)
>> 'data.frame': 80 obs. of 4 variables:
>> $ Location: Factor w/ 4 levels "Cies1","Cies2",..: 1 1 1 1 1 1 1 1 1 1
>> ...
>> $ Protection: Factor w/ 2 levels "Control","Protected": 1 1 1 1 1 2 2 2 2
>> 2 ...
>> $ Exposure: Factor w/ 2 levels "Exposed","Semiexposed": 1 1 1 1 1 1 1 1 1
>> 1 ...
>> $ Biomass: num 124.8 104.8 139.2 102.6 62.9 ...
>>
>>
>> First I ran it as a Poission distribution (after round the Biomass values)
>> to be able to fit a zeroInflation model:
>> > Model_ADMB_P<-glmmadmb(Biomass~Protection+Exposure+Protectio
>> n:Exposure+(1|
>> Protection/Location),data=GLMMADMB_P, zeroInflation=TRUE,
>> family="Poisson")
>> Parameters were estimated, but standard errors were not: the most likely
>> problem is that the curvature at MLE was zero or negative
>> Error in glmmadmb(Biomass ~ Protection + Exposure + Protection:Exposure +
>> :
>> The function maximizer failed (couldn't find parameter file)
>> Troubleshooting steps include (1) run with 'save.dir' set and inspect
>> output files; (2) change run parameters: see '?admbControl';(3) re-run
>> with
>> debug=TRUE for more information on failure mode
>> Además: Warning message:
>> comando ejecutado 'C:\WINDOWS\system32\cmd.exe /c glmmadmb -maxfn 500
>> -maxph 5 -noinit -shess' tiene estatus 1
>>
>> Then I though that since my data is continuous I'd better run the model
>> with a gamma family, however, when I do run it with gamma I got the
>> following error:
>> > Model_ADMB_G<-glmmadmb(Biomass~Protection+Exposure+Protectio
>> n:Exposure+(1|
>> Protection/Location),data=GLMMADMB_P, family="gamma")
>>
>> Error in glmmadmb(Biomass ~ Protection + Exposure + Protection:Exposure +
>> :
>> The function maximizer failed (couldn't find parameter file)
>> Troubleshooting steps include (1) run with 'save.dir' set and inspect
>> output files; (2) change run parameters: see '?admbControl';(3) re-run
>> with
>> debug=TRUE for more information on failure mode
>> Además: Warning message:
>> comando ejecutado 'C:\WINDOWS\system32\cmd.exe /c glmmadmb -maxfn 500
>> -maxph 5 -noinit -shess' tiene estatus 1
>>
>> However, when I run it as a Poisson distribution with zeroInflated values
>> but with no nested design and Location effect either, it ran ok
>> > Model_ADMB_P1<-glmmadmb(Biomass~Protection*Exposure,data=GLMMADMB_P,
>> zeroInflation=TRUE, family="Poisson")
>> > summary(Model_ADMB_P1)
>>
>> Call:
>> glmmadmb(formula = Biomass ~ Protection * Exposure, data = GLMMADMB_P,
>> family = "Poisson", zeroInflation = TRUE)
>>
>> AIC: 1570.7
>>
>> Coefficients:
>> Estimate Std. Error z value
>> Pr(>|z|)
>> (Intercept) 4.71e+00 3.18e-02 148.0
>> <2e-16
>> ProtectionProtected -5.53e-01 5.00e-02 -11.1
>> <2e-16
>> ExposureSemiexposed -3.83e+01 2.22e+05 0.0
>> 1
>> ProtectionProtected:ExposureSemiexposed 3.64e+01 2.22e+05 0.0
>> 1
>>
>> (Intercept) ***
>> ProtectionProtected ***
>> ExposureSemiexposed
>> ProtectionProtected:ExposureSemiexposed
>> ---
>> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>>
>> Number of observations: total=80
>> Zero-inflation: 0.30908 (std. err.: 0.071433 )
>>
>> Log-likelihood: -780.37
>> >
>>
>>
>> I can not understat the solutions to these errors, can anyone please help
>> me out?
>> I really appreciate it!
>>
>> Thanks in advance,
>>
>> --
>> Andreu Blanco Cartagena
>>
>>
>>
>> Si no és imprescindible, no imprimeixis aquest e-mail. Estalviar paper
>> ajuda a protegir el medi ambient.
>>
>> Si no es imprescindible, no imprimas este e-mail. Ahorrar papel ayuda a
>> proteger el medio ambiente.
>>
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>>
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>
>
>
--
Andreu Blanco Cartagena
Si no és imprescindible, no imprimeixis aquest e-mail. Estalviar paper
ajuda a protegir el medi ambient.
Si no es imprescindible, no imprimas este e-mail. Ahorrar papel ayuda a
proteger el medio ambiente.
[[alternative HTML version deleted]]
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