Penalized likelihood methods improve parameter estimates in occupancy models
Abstract
Occupancy models are employed in species distribution modelling to account for imperfect detection during field surveys. While this approach is popular in the literature, problems can occur when estimating the model parameters. In particular, the maximum likelihood estimates can exhibit bias and large variance for data sets with small sample sizes, which can result in estimated occupancy probabilities near 0 and 1 (‘boundary estimates’).
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 31, 2015
- Source ID
- 10.1111/2041-210x.12368
Entities
People
- Jonathon J Valente
- Matthew G. Betts
- Rebecca A. Hutchinson
- Sarah C. Emerson
- Thomas G. Dietterich
Organizations
- National Science Foundation
- Oregon State University
- United States Department of Defense