Bayesian Applications in Environmental and Ecological Studies with R and Stan

You must be logged in to access this title.

Sign up now

Already a member? Log in

Synopsis

Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data.
Features• An accessible overview of Bayesian methods in environmental and ecological studies• Emphasizes the hypothetical deductive process, particularly model formulation• Necessary background material on Bayesian inference and Monte Carlo simulation• Detailed case studies, covering water quality monitoring and assessment, ecosystem response to urbanization, fisheries ecology, and more• Advanced chapter on Bayesian applications, including Bayesian networks and a change point model• Complete code for all examples, along with the data used in the book, are available via GitHub
The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.

Book details

Series:
Chapman & Hall/CRC Applied Environmental Statistics
Author:
Song S. Qian, Mark R. DuFour, Ibrahim Alameddine
ISBN:
9781351018760
Related ISBNs:
9781351018784, 9781138497399, 9781032290072
Publisher:
CRC Press
Pages:
395
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2022-08-16
Usage restrictions:
Copyright
Copyright date:
2022
Copyright by:
Taylor & Francis Group, LLC 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Medicine, Nonfiction