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richness
2011 Jan 27
1
Quasi-poisson glm and calculating a qAIC and qAICc...trying to modilfy Bolker et al. 2009 function to work for a glm model
...ances. For example, my beetle
richness is overdispersed:
> qcc.overdispersion.test(beetle.richness)
Overdispersion test Obs.Var/Theor.Var Statistic p-value
poisson data 2.628131 23.65318 0.0048847
So, I am running a simple glm with my distribution as quasipoisson
> glm.richness1<-glm(beetle.richness~log.area, family = quasipoisson)
Now I want to calculate a qAIC and qAICc. I was trying to modify the
equation that I found in Bolker et al 2009 supplemental material:
QAICc <- function(mod, scale, QAICc=TRUE){
LL <- logLik(mod)
ll <- as.numeric(...