OUTLINE 1. Intro 2. Two-sample case: 1. clear description of two sample case, study design characteristics, and data type(s) 2. Point process formulation in Warton and McDonald papers 3. Example 3. Discrete choice case 1. clear description of the discrete choice case, study design characteristics, and data type(s) 2. Summarize McDonald et al owl paper 3. Variance estimation with multiple animals (bootstrapping/mixed models/Bayesian methods) 4. Example (DC software has come a long ways since the yellow book, we will need to review software) 4. Count model case (Negative binomial) 1. clear description of the case, study design characteristics, and data type(s) 2. Summarize Nielson-Sawyer and Millspaugh papers. Include relationship of this approach to MAXINT model (Warton paper). 3. Variance estimation with multiple animals (bootstrapping/mixed models/Bayesian methods) 4. Example (perhaps NB and MAXINT models fitted to same data set). 5. Radio-telemetry with missing observation case 1. clear description of the case, study design characteristics, and data type(s) 2. Summarize Nielson paper. (Do we have a Markov-type movement model fully integrated into the selection process?) 3. Example