State-space models’ dirty little secrets: even simple linear Gaussian models can have estimation problems

State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They...

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Detalles Bibliográficos
Autores principales: Auger-Méthé, Marie, Field, Chris, Albertsen, Christoffer M., Derocher, Andrew E., Lewis, Mark A., Jonsen, Ian D., Mills Flemming, Joanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879567/
https://www.ncbi.nlm.nih.gov/pubmed/27220686
http://dx.doi.org/10.1038/srep26677

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879567/
https://www.ncbi.nlm.nih.gov/pubmed/27220686
http://dx.doi.org/10.1038/srep26677

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