[R-sig-ME] multiple errors when using glmmADMB
Bansal, Udita
udit@@b@n@@l17 @ending from imperi@l@@c@uk
Fri Jul 27 12:41:15 CEST 2018
Hi Mollie,
Thanks again for the ideas and explanation. I am not sure about how to interpret the output from the DHARMa package. I got the graph attached herewith.
I had run a few models with glmmTMB and a simple one with glmer.
m_tmb <- glmmTMB(breeding.success ~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR) ,
data = hungary_breeding, ziformula = ~1, family = binomial, weights = CSIZE)
tmb_poisson <- glmmTMB(breeding.success ~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR) ,
data = hungary_breeding, ziformula = ~1, family = poisson)
tmb_nbinom1 <- glmmTMB(breeding.success ~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR) ,
data = hungary_breeding, ziformula = ~1, family = nbinom1)
## Warning message: In fitTMB(TMBStruc) : Model convergence problem; false convergence (8). See vignette('troubleshooting')
tmb_nbinom2 <- glmmTMB(breeding.success ~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR) ,
data = hungary_breeding, ziformula = ~1, family = nbinom2) ## same warning as above
gm1 <- glmer(breeding.success ~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR) ,
data = hungary_breeding, family = binomial, weights = CSIZE)
The AIC looks as follows:
AIC(m_tmb, tmb_poisson, tmb_nbinom1, tmb_nbinom2, gm1)
df AIC
m_tmb 5 489.2653
tmb_poisson 5 333.4137
tmb_nbinom1 6 335.3694
tmb_nbinom2 6 335.4137
gm1 4 764.4029
This makes me think it should one of the models with the lower AIC?
Thanks
Udita
On 27/07/18, 10:52 AM, "Mollie Brooks" <mollieebrooks using gmail.com> wrote:
Hi Udita,
It’s unlikely (but possible) that you’ll need to handle zero inflation. You could test for it using the DHARMa package. Here’s an example of doing that with binomial data.
library(DHARMa)
library(lme4)
gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
data = cbpp, family = binomial)
simulationOutput <- simulateResiduals(fittedModel = gm1, n=1000)
testZeroInflation(simulationOutput)
If you do have zero-inflation, then you could use glmmTMB for models like this
#nest failure equally possible for all observations
m1 <- glmmTMB(cbind(No.of.chicks, Clutch.size-No.of.chicks)~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR), zi=~1, data = hungary_breeding, , family = binomial)
#nest failure varies randomly by year
m2 <- glmmTMB(cbind(No.of.chicks, Clutch.size-No.of.chicks)~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR), zi=~(1|YEAR), data = hungary_breeding, , family = binomial)
#nest failure varies with tmean.zscale
m3 <- glmmTMB(cbind(No.of.chicks, Clutch.size-No.of.chicks)~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR), zi=~ tmean.zscale, data = hungary_breeding, , family = binomial)
cheers,
Mollie
> On 27Jul 2018, at 11:28, Bansal, Udita <udita.bansal17 using imperial.ac.uk> wrote:
>
> Hi Mollie,
>
> Thanks a lot, I have tried that and it runs the model. My concern is that I cannot include zero inflation of the data in this model. Any ideas for that?
>
> Cheers
> Udita
>
> On 27/07/18, 9:47 AM, "Mollie Brooks" <mollieebrooks using gmail.com> wrote:
>
> Hi Udita,
>
> It looks like this is binomial data. You probably want logistic regression like this
>
> library(lme4)
> m_glmer <- glmer(cbind(No.of.chicks, Clutch.size-No.of.chicks)~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR), data = hungary_breeding, , family = binomial)
>
> cheers,
> Mollie
>
>> On 26Jul 2018, at 22:03, Bansal, Udita <udita.bansal17 using imperial.ac.uk> wrote:
>>
>> I am measuring breeding success as number of chicks produced out of number of eggs laid. So, the values range from 0 to 1 including decimal values. Although, that was just a warning. Should I be too concerned about that?
>>
>> My model statement is as follows:
>> m_admb <- glmmadmb( breeding.success ~ laying.date.julian.day.zscale + tmean.zscale + (1|YEAR) ,
>> data = hungary_breeding, zeroInflation = TRUE, family = "nbinom", link = "logit")
>>
>> Summary for relevant columns of my data:
>>
>> YEAR No.of.chicks Clutch.size laying_date tmean prec
>> 1988:16 Min. :0.000 Min. :2.000 Min. :1988-04-22 Min. : 3.45 Min. : 0.000
>> 1989:25 1st Qu.:0.000 1st Qu.:3.000 1st Qu.:1990-05-07 1st Qu.:11.35 1st Qu.: 0.000
>> 1990:45 Median :0.000 Median :3.000 Median :1991-05-09 Median :15.12 Median : 0.000
>> 1991:65 Mean :1.021 Mean :2.946 Mean :1991-05-24 Mean :14.62 Mean : 2.285
>> 1992:46 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:1992-05-15 3rd Qu.:17.95 3rd Qu.: 1.050
>> 1993:24 Max. :3.000 Max. :3.000 Max. :1994-06-16 Max. :27.05 Max. :55.200
>> 1994:19
>> breeding.success clutch.volume laying.date.julian.day tmean.zscale.V1 prec.zscale.V1
>> Min. :0.0000 Min. :15.82 Min. : 82.0 Min. :-2.5607265 Min. :-0.559014
>> 1st Qu.:0.0000 1st Qu.:24.60 1st Qu.:115.0 1st Qu.:-0.7638887 1st Qu.:-0.559014
>> Median :0.0000 Median :25.89 Median :129.0 Median : 0.0947269 Median :-0.559014
>> Mean :0.3438 Mean :25.52 Mean :132.3 Mean :-0.0190444 Mean : 0.006583
>> 3rd Qu.:1.0000 3rd Qu.:27.06 3rd Qu.:148.2 3rd Qu.: 0.7372670 3rd Qu.: 0.209975
>> Max. :1.0000 Max. :29.83 Max. :186.0 Max. : 2.8070422 Max. : 3.762186
>>
>> laying.date.julian.day.zscale.V1
>> Min. :-2.2850626
>> 1st Qu.:-0.7846733
>> Median :-0.1481445
>> Mean : 0.0000000
>> 3rd Qu.: 0.7270826
>> Max. : 2.4434370
>>
>> I will try glmmTMB as well now.
>>
>> Thanks
>> Udita
>>
>> On 26/07/18, 7:41 PM, "R-sig-mixed-models on behalf of Ben Bolker" <r-sig-mixed-models-bounces using r-project.org on behalf of bbolker using gmail.com> wrote:
>>
>>
>> The first thing that pops out is the "non-integer response values in
>> discrete family" warning. How are you measuring breeding success? Can
>> you show us your whole glmmadmb() statement, and maybe a summary() of
>> the relevant columns of your data set?
>>
>> I'll also make the now-blanket statement that you may have better
>> luck moving forward with glmmTMB.
>>
>> cheers
>> Ben Bolker
>>
>> On 2018-07-26 12:57 PM, Bansal, Udita wrote:
>>> Hi all,
>>>
>>> I was trying to use the glmmADMB package but ran into some errors. I’ve
>>> noticed that other people have run into similar errors but there doesn’t
>>> seem to be a solution online. It would be great help if anyone could
>>> provide any insights on it.
>>>
>>> I am using it for running a zero-inflated mixed-effects binomial model.
>>> The errors are as follows:
>>>
>>> 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(breeding.success ~ laying.date.julian.day.zscale +
>>> tmean.zscale + :
>>> 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
>>> In addition: Warning messages:
>>> 1: In glmmadmb(breeding.success ~ laying.date.julian.day.zscale +
>>> tmean.zscale + :
>>> non-integer response values in discrete family
>>> 2: running command './glmmadmb -maxfn 500 -maxph 5 -noinit -shess' had
>>> status 1
>>>
>>> Any kind of help will be greatly appreciated.
>>>
>>> Bests
>>> Udita Bansal
>>>
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> _______________________________________________
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>>>
>>
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