Bayesian Analysis of Spatially Structured Population Dynamics
The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in our changing world. Several chapters are devoted to introducing models that utilize detection/non-detection data, count data, combined count and capture...
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| 第一著者: | |
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| 団体著者: | |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Cham :
Springer International Publishing : Imprint: Springer,
2024.
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| 版: | 1st ed. 2024. |
| シリーズ: | Ecological Studies, Analysis and Synthesis,
253 |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-3-031-64518-1 |
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| 要約: | The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in our changing world. Several chapters are devoted to introducing models that utilize detection/non-detection data, count data, combined count and capture-recapture data, and spatial capture-recapture data, respectively. The book provides R code of Metropolis-Hastings algorithms that allow efficient computing of these complex models. The book is aimed at graduate students and researchers who are interested in using and further developing these models. |
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| 物理的記述: | 1 online resource (XVI, 386 p. 58 illus.). 58 illus. in color. |
| ISBN: | 9783031645181 |
| ISSN: | 2196-971X ; |
| DOI: | 10.1007/978-3-031-64518-1 |