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Hierarchical modelling for the environmental sciences : statistical methods and applications /

' ... if you are already quite well acquainted with Bayesian concepts and terminology then this book should provide an excellent guide to the application of these advanced statistical techniques within ecology.' Justin Travis, Bulletin of the British Ecological Society 2007 38:1 -

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Clark, James Samuel, 1957-, Gelfand, Alan E., 1945-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Oxford ; New York : Oxford University Press, 2006.
Colección:Oxford biology.
Temas:
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Part I. Introduction to hierarchical modeling
  • Elements of hierarchical Bayesian inference / Bradley P. Carlin, James S. Clark, and Alan E. Gelfand
  • Bayesian hierarchical models in geographical genetics / Kent E. Holsinger
  • Part II. Hierarchical models in experimental settings
  • Synthesizing ecological experiments and observational data with hierarchical Bayes / James S. Clark and Shannon LaDeau
  • Effects of global change on inflorescence production: a Bayesian hierarchical analysis / Janneke Hille Ris Lambers, Brian Aukema, Jeff Diez, Margaret Evans, and Andrew Latimer
  • Part II. Spatial modeling
  • Building statistical models to analyze species distributions / Alan E. Gelfand, Andrew Latimer, Shanshan Wu, and John A Silander, Jr
  • Implications of vulnerability to hurricane damage for long-term survival of tropical tree species: a Bayesian hierarchical analysis / Kiona Ogle, María Uriarte, Jill Thompson, Jill Johnstone, Andy Jones, Yiching Lin, Eliot J.B. McIntire, and Jess K. Zimmerman
  • Part IV. Spatio-temporal modeling
  • Spatial-temporal statistical modeling and prediction of environmental processes / Li Chen, Montserrat Fuentes, and Jerry M. Davis
  • Hierarchical Bayesian spatio-temporal models for population spread / Christopher K. Wikle and Mevin B. Hooten
  • Spatial models for the distribution of extremes / Eric Gilleland, Douglas Nychka and Uli Schneider.