Introduction to Hierarchical Bayesian Modeling for Ecological Data - Couverture souple

Parent, Eric

Couverture souple

ISBN 10 : 0367576716 ISBN 13 : 9780367576714

Editeur : Routledge, 2020

Synopsis

Making statistical modeling and inference more accessible to ecologists and related scientists, this book gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competi

A propos du livre

À propos de l?auteur

Éric Parent is head of the Research Laboratory for Risk Management in Environmental Sciences (Team MORSE) and a professor in applied statistics and probabilistic modeling for environmental engineering at the National Institute for Rural Engineering, Water and Forest Management (ENGREF/AgroParisTech) in Paris, France. Dr. Parent's research encompasses Bayesian theory and applications, with special emphasis on environmental systems modeling.

Étienne Rivot is a researcher in the Fisheries Ecology Laboratory at Agrocampus Ouest in Rennes, France. Dr. Rivot's research focuses on the application of Bayesian statistical modeling for the analysis of ecological data, inference, and predictions.

Détails de l'édition

• Éditeur: Routledge
• Date d'édition: 2020
• Langue: anglais
• ISBN 10: 0367576716
• ISBN 13: 9780367576714
• Reliure: Broché
• Nombre de pages: 428
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible