Re: [R] Logistic regression model selection with overdispersed/autocorrelated data

Thanks for pointing out the aod package and the beta-binomial logistic models Renaud. While I see how betabinom could be applied to some of our other analyses , I don't see how it can be used in our habitat selection analysis where individual locations are coded as 0 or 1 rather than

Re: [R] Logistic regression model selection with overdispersed/autocorrelated data

[EMAIL PROTECTED] wrote: I am creating habitat selection models for caribou and other species with data collected from GPS collars. In my current situation the radio-collars recorded the locations of 30 caribou every 6 hours. I am then comparing resources used at caribou locations to

[R] Logistic regression model selection with overdispersed/autocorrelated data

I am creating habitat selection models for caribou and other species with data collected from GPS collars. In my current situation the radio-collars recorded the locations of 30 caribou every 6 hours. I am then comparing resources used at caribou locations to random locations using logistic

[R] hypergeometric population estimates

help We want to estimate the number of caribou in Jasper. We recently conducted an aerial survey and saw 70 uncollared caribou and 8 of 11 collared caribou. We want to estimate the number of caribou in this population with 95% confidence limits. Gary White uses the hypergeometric distribution