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Autor(en): 
  • Marc Kéry
  • Kenneth F. Kellner
  • Applied Statistical Modelling for Ecologists: A Practical Guide to Bayesian and Likelihood Inference Using R, JAGS, NIMBLE, Stan and TMB 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2024  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Applied ecology / applied statistical modelling / Applied Statistics / bayesian modeling / Ecological science, the Biosphere / Ecology / Linear Models / Mathematical modelling
    ISBN:  9780443137150 
    EAN-Code: 
    9780443137150 
    Verlag:  Elsevier 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 191 mm / D 30 mm 
    Gewicht:  1100 gr 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    **2025 PROSE Award Finalist in Environmental Science**

    Applied Statistical Modelling for Ecologists provides a gentle introduction to the essential models of applied statistics: linear models, generalized linear models, mixed and hierarchical models. All models are fit with both a likelihood and a Bayesian approach, using several powerful software packages widely used in research publications: JAGS, NIMBLE, Stan, and TMB. In addition, the foundational method of maximum likelihood is explained in a manner that ecologists can really understand.

    This book is the successor of the widely used Introduction to WinBUGS for Ecologists (Kéry, Academic Press, 2010). Like its parent, it is extremely effective for both classroom use and self-study, allowing students and researchers alike to quickly learn, understand, and carry out a very wide range of statistical modelling tasks.

    The examples in Applied Statistical Modelling for Ecologists come from ecology and the environmental sciences, but the underlying statistical models are very widely used by scientists across many disciplines. This book will be useful for anybody who needs to learn and quickly become proficient in statistical modelling, with either a likelihood or a Bayesian focus, and in the model-fitting engines covered, including the three latest packages NIMBLE, Stan, and TMB.

      



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