If you?re interested, you could also give a try in the GLMMadaptive package that can also fit zero-inflated and two-part/hurdle models under maximum likelihood using the adaptive Gaussian quadrature rule.
For more info check: https://drizopoulos.github.io/GLMMadaptive/articles/ZeroInflated_and_TwoPart_Models.html
Best,
Dimitris
- - - - - -
Dimitris Rizopoulos
Professor of Biostatistics
Erasmus University Medical Center
The Netherlands
From: C. AMAL D. GLELE <altessedac2 at gmail.com<mailto:altessedac2 at gmail.com>>
Date: Saturday, 25 Aug 2018, 9:38 PM
To: R SIG Mixed Models <r-sig-mixed-models at r-project.org<mailto:r-sig-mixed-models at r-project.org>>
Subject: [R-sig-ME] glmmadmb_problem: "sd.est not defined for this family"
Hi, dear all.
When fitting models with glmmadmb, I'm encountering the following problems:
Problem1
I've fitted "mymodel" using glmmadmb with family="troncnbinom1";
the model fits, but with the following warning:
"In eval(substitute(expr), data, enclos = parent.frame()) :
sd.est not defined for this family"
summary() shows correctly the outputs, but residuals(mymodel) gives only
"NA";
the same problem occurs when family="troncnbinom"
Problem2
I've fitted "mymodel2" using glmmadmb, with family"poisson"; it has fitted
well(without neither error, nor warning)
but, plot.glmmadmb() sent "couldn't see function plot.glmmadmb";
in add, VarCorr(mymodel2) is giving me only intercepts variance, although
I've included random slope in the model.
Taking a look at the "troubleshooting" session of "glmmadmb_manual" did not
help me solving these problems.
In advance, thanks for your helps.
Kind regards,
Amal
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