Uncovering ecological state dynamics with hidden Markov models-Reference-Cited by-同舟云学术

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Uncovering ecological state dynamics with hidden Markov models

Published:2020-10-19 Issue:12 Volume:23 Page:1878-1903
ISSN:1461-023X
Container-title:Ecology Letters
language:en
Short-container-title:Ecol. Lett.

Author:

McClintock Brett T.¹^ORCID,Langrock Roland²,Gimenez Olivier³,Cam Emmanuelle⁴,Borchers David L.⁵,Glennie Richard⁵,Patterson Toby A.⁶^ORCID

Affiliation:

1. NOAA National Marine Fisheries Service Seattle WA USA

2. Department of Business Administration and Economics Bielefeld University Bielefeld Germany

3. CNRS Centre d'Ecologie Fonctionnelle et Evolutive Montpellier France

4. Laboratoire des Sciences de l'Environnement Marin Institut Universitaire Européen de la Mer Univ. BrestCNRS, IRD Ifremer France

5. School of Mathematics and Statistics University of St Andrews St Andrews UK

6. CSIRO Oceans and Atmosphere Hobart Australia

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ele.13610

Reference275 articles.

1. Improving the consistency of multitemporal land cover maps using a hidden Markov model;Abercrombie S.P.;IEEE Trans. Geosci. Remote Sens.,2015

2. Joint modelling of multi‐scale animal movement data using hierarchical hidden Markov models

3. Penalized estimation of flexible hidden Markov models for time series of counts

4. Mixed Hidden Markov Models

5. A continuous-time hidden Markov model for cancer surveillance using serum biomarkers with application to hepatocellular carcinoma

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