Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

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Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).
Publication type Article
Publication Subtype Journal Article
Title Estimating parameters of hidden Markov models based on marked individuals: use of robust design data
Series title Ecology
DOI 10.1890/11-1538.1
Volume 93
Issue 4
Year Published 2012
Language English
Publisher Ecological Society of America
Publisher location Ithaca, NY
Contributing office(s) Patuxent Wildlife Research Center
Description 8 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Ecology
First page 913
Last page 920
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