I am attempting to perform multi-season occupancy modeling in RPresence. I haven't been able to find any tutorials or walkthroughs for performing occupancy modeling with RPresence and have been figuring it out mainly through trial and error. It is very plausible that I have made a mistake somewhere in my code and haven't detected it. In order to "confirm" that I was performing the analysis correctly I used the same .pao and performed the same analysis in RPresence and in the Presence software. I first noticed the difference in my own data and assumed that it was an error within my dataset. I then took a step back and followed the guided instructions for the northern saw-whet owl example. I am making the assumption that the default option for Presence, psi(.),gamma(.),eps(.)p(.), would provide the same results as this code in RPresence:
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NSOPao<-readPao('nso.pao')
mod1<- occMod(model=list (psi~1, gamma~1,epsilon~1, p~1),data= NSOPao, type= "do.1")
When I compared the outputs of these models the AIC values were the same as well as the psi,gamma, and epsilon values.However, the p values were not the same. The Rpresence output help p at .49474 and the Presence output started at .49474 and had some missing values and then some random numbers throughout.
Can anyone please explain to me where I could have went wrong?
Thank you,
Devin