Question - frequency weighted availability

[coverton-usgs]

I have a rather unique dataset, multiple millions of GPS locations in a constrained environment making determination of categorical habitat availability pretty straightforward and which are summarized in a frequency table. I can reasonably assume that all habitats are available given the movement capabilities of the species studied and generating 10-fold random selections to contrast with the used data would result in over a hundred million records which is beyond my compute capacity.

Is it appropriate to run rsf or rspf functions using a weights function that is =1 for used cases and =Frequency of occurrence for available cases? This would essentially limit the rows of available data to 1 per class.

The simulation I just ran produces identical estimates whether I use weights = Freq or not, the Standard errors are different, but I expect that is due to just using a few bootstraps as a trial run.

[psolymos]

Hi @coverton-usgs the weights has no effect on the rsf and rspf outputs because it is not passed to the function being optimized. You can

• subset the data set to minimize the redundancy while also keeping the proportions for the available part of the data
• use the glm function instead bit the logit link

HTH