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Improving inference for nonlinear state‐space models of animal population dynamics given biased sequential life stage data
State‐space models (SSMs) are a popular tool for modeling animal abundances. Inference difficulties for simple linear SSMs are well known, particularly in relation to simultaneous estimation of process and observation variances. Several remedies to overcome estimation problems have been studied for...
Autores principales: | Polansky, Leo, Newman, Ken B., Mitchell, Lara |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984174/ https://www.ncbi.nlm.nih.gov/pubmed/32243577 http://dx.doi.org/10.1111/biom.13267 |
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