Multievent: An Extension of Multistate Capture–Recapture Models to Uncertain States

Biometrics - Tập 61 Số 2 - Trang 442-447 - 2005
Roger Pradel1
1CEFE, UMR 5175, 1919 Route de Mende, F-34293 Montpellier, Cedex 05, France email:[email protected]

Tóm tắt

Summary Capture–recapture models were originally developed to account for encounter probabilities that are less than 1 in free‐ranging animal populations. Nowadays, these models can deal with the movement of animals between different locations and are also used to study transitions between different states. However, their use to estimate transitions between states does not account for uncertainty in state assignment. I present the extension of multievent models, which does incorporate this uncertainty. Multievent models belong to the family of hidden Markov models. I also show in this article that the memory model, in which the next state or location is influenced by the previous state occupied, can be fully treated within the framework of multievent models.

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Tài liệu tham khảo

10.1007/BF02521971

10.1007/BF02510705

10.1214/aoms/1177699147

10.2307/2532259

10.1093/biomet/84.1.187

Dupuis J. A., 1995, Bayesian estimation of movement and survival probabilities from capture–recapture data, Biometrika, 82, 761

10.1890/0012-9658(2002)083[3257:EPPMFM]2.0.CO;2

10.1002/bimj.200390043

Hanselman D., 2000, Mastering MATLAB 6

10.2307/2937193

10.1890/0012-9658(2003)084[1058:AMCMFM]2.0.CO;2

10.1080/02664769524766

10.1080/02664760120108638

10.1080/00063659909477230

MacDonald I. L., 1997, Hidden Markov and Other Models for Discrete‐Valued Time Series

10.1007/978-1-4899-3244-0

10.2307/1941610

10.1111/j.0006-341X.2003.00092.x

10.1111/1541-0420.00006

Rabiner L. R., 1993, Fundamentals of Speech Recognition

10.1214/ss/1009212521