Bayesian Analysis of Spatially Structured Population Dynamics
Okt 2024 · Ecological Studies Ibhuku elingu-253 · Springer Nature
I-Ebook
386
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reportIzilinganiso nezibuyekezo aziqinisekisiwe Funda Kabanzi
Mayelana nale ebook
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.
Mayelana nomlobi
Qing Zhao is a quantitative ecologist with strong interests in developing and applying statistical models to understand and predict how animal populations, communities and movement respond to our changing world. He has worked closely with conservation agencies for more than 10 years to broaden the impacts of his research on biodiversity conservation at local, regional, and international scales.
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