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 $disp NULL ## m1<-glmmTMB(sp2~Grazing+(1|Plot)+(1|Plot:Grazing),data=biomass[biomass$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 canĀ“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 [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology