Statistical Models Commons^™

A Bayesian Hierarchical Mixture Model With Continuous-Time Markov Chains To Capture Bumblebee Foraging Behavior, Max Thrush Hukill

Honors Projects

The standard statistical methodology for analyzing complex case-control studies in ethology is often limited by approaches that force researchers to model distinct aspects of biological processes in a piecemeal, disjointed fashion. By developing a hierarchical Bayesian model, this work demonstrates that statistical inference in this context can be done using a single coherent framework. To do this, we construct a continuous-time Markov chain (CTMC) to model bumblebee foraging behavior. To connect the experimental design with the CTMC, we employ a mixture model controlled by a logistic regression on the two-factor design matrix. We then show how to infer these model …

Seasonal Resource Selection And Habitat Treatment Use By A Fringe Population Of Greater Sage-Grouse, Rhett Boswell

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Movement and habitat selection by Greater Sage-grouse (Centrocercus uropasianus) is of great interest to wildlife managers tasked with applying conservation measures for this iconic western species. Current technology has created small and lightweight GPS (Global Positioning Systems) transmitters that can be attached to sage-grouse. Using GIS software and statistical programs such as Program R, land managers can analyze GPS location data to assess how sage-grouse are geospatially interacting with their habitats. Within the Panguitch Sage-Grouse Management Area (SGMA) thousands of acres of land have been restored or manipulated to enhance sage-grouse habitat; this usually involves removal of pinyon pine …

Identifying The Spatial Distribution Of Three Plethodontid Salamanders In Great Smoky Mountains National Park Using Two Habitat Modeling Methods, Matthew Stephen Kookogey

Masters Theses

The main objective was to create habitat models of three plethodontid salamander species (Desmognathus conanti, D. ocoee, and Plethodon jordani) in GSMNP. To investigate the relationships between salamanders and their habitats, I used three models—logistic regression with use-availability sampling, logistic regression with case-control sampling, and Mahalanobis distance (D²)—for each species to gain a robust view of the relationships. The secondary objective was to compare the different modeling methods within and across the three species. Elevation was the dominant variable for all three species.

D² for D. conanti predicted low elevations, close proximity …