Eric Parent, Etienne Rivot

eBook, PDF

Introduction to Hierarchical Bayesian Modeling for Ecological Data (eBook, PDF)

Beschreibung

Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statisti

Technische Details

• Geräte: PC
• mit Kopierschutz
• Größe: 5.43MB

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• Seitennummerierung folgt dem gedruckten Werk
• Kurze Alternativtexte für nicht-textuelle Inhalte vorhanden
• Navigierbarer Index mit direktem Zugriff auf Indexbegriffe
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien

Autor

eric 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.

etienne 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.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 427
• Erscheinungstermin: 21. August 2012
• Englisch
• ISBN-13: 9781584889205
• Artikelnr.: 39487288