Does spOccupancy fit basic logistic regression models (without incorporating a detectability process)?

[Javi Fernández-López]

Sorry for what might be a somewhat silly question, but I wanted to know whether, just as spAbundance fits GLMMs with NB, Gaussian, Poisson, etc. families without a detectability process, spOccupancy can also do that. I haven’t found any function for this purpose, and I’m not sure if by 'forcing' the Occ functions through priors I could achieve something equivalent.

I was simply hoping to take advantage of the effective machinery in spOccupancy for fitting spatial logistic models.

Best regards, and thanks in advance!

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Javier Fernández-López

Assistant Professor at Universidad Complutense de Madrid, Spain

Area of Biomathematics, Department of Biodiversity, Ecology and Evolution

https://jabiologo.github.io/web/index.html

[Jeffrey Doser]

Hi Javi, 

Thanks for the note. You can fit a spatial logistic model in spOccupancy using the svcPGBinom function. That function is designed to fit spatially varying coefficient models without imperfect detection for binary or binomial data, but if you just want to fit a spatial logistic model, you could set svc.cols = 1. I will mention that there is no function for a non-spatial basic logistic regression model, but of course a Bayesian logistic regression model could be fit very quickly with brms or something of that nature. 

Hope you're doing well!

Jeff

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Jeffrey W. Doser, Ph.D.

Assistant Professor

Department of Forestry and Environmental Resources

North Carolina State University

Statistical Ecology and Forest Science Lab

Pronouns: he/him/his

[Javi Fernández-López]

Awesome Jeff, thanks a lot and sorry for bothering you!

 Best!