Bayesian Analysis of Spatially Structured Population Dynamics: Ecological Studies, cartea 253
Autor Qing Zhaoen Limba Engleză Hardback – 12 sep 2024
Din seria Ecological Studies
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Specificații
ISBN-13: 9783031645174
ISBN-10: 3031645170
Pagini: 130
Ilustrații: Approx. 130 p. 10 illus.
Dimensiuni: 155 x 235 mm
Ediția:2024
Editura: Springer International Publishing
Colecția Springer
Seria Ecological Studies
Locul publicării:Cham, Switzerland
ISBN-10: 3031645170
Pagini: 130
Ilustrații: Approx. 130 p. 10 illus.
Dimensiuni: 155 x 235 mm
Ediția:2024
Editura: Springer International Publishing
Colecția Springer
Seria Ecological Studies
Locul publicării:Cham, Switzerland
Cuprins
Chapter 1: Background.- Chapter 2: Occupancy Models.- Chapter 3: N-mixture models.- Chapter 4: Integrated population models (IPMs).- Chapter 5: Spatial capture-recapture (SCR) models.- Chapter 6: Summary and outlook.
Notă biografică
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.
Textul de pe ultima copertă
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-Hasting 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.
Caracteristici
Synthesizes a vast and diverse set of advanced statistical tools for modeling spatially structured population dynamics Provides sufficiently detailed R code for applying and further developing these models Illustrates the presentation of modeling results with elegant graphs