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Comparing N-mixture models and GLMMs for relative abundance estimation in a citizen science dataset
To analyze species count data when detection is imperfect, ecologists need models to estimate relative abundance in the presence of unknown sources of heterogeneity. Two candidate models are generalized linear mixed models (GLMMs) and hierarchical N-mixture models. GLMMs are computationally robust b...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296480/ https://www.ncbi.nlm.nih.gov/pubmed/35853908 http://dx.doi.org/10.1038/s41598-022-16368-z |