Accounting for misidentification and heterogeneity in occupancy studies using hidden Markov models
Abstract
Occupancy models allow assessing species occurrence while accounting for imperfect detection. As with any statistical models, occupancy models rely on several assumptions amongst which (i) there should be no unmodelled heterogeneity in the detection probability and (ii) the species should not be detected when absent from a site, in other words there should be no false positives (e.g., due to misidentification). In the real world, these two...
Paper Details
Title
Accounting for misidentification and heterogeneity in occupancy studies using hidden Markov models
Published Date
Nov 1, 2018
Journal
Volume
387
Pages
61 - 69
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History