Sahu, Sujit

Bayesian Modeling of Spatio-Temporal Data with R (Chapman & Hall/CRC Interdisciplinary Statistics)

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ISBN 13:
9781032209579
author:
Sahu, Sujit
format:
Paperback
publisher:
CRC Press
language:
English
Publication Year:
2024
Pages:
434
Dimensions:
23.4 x 15.4 x 2 centimetres (0.7
Genre:
Science, Mathematics, Statistics,
Condition:
New
Availability:
Item usually sent within 10 working days
£53.14

Description

Bayesian Modeling of Spatio-Temporal Data with R provides a comprehensive guide to unlocking the full power of Bayesian methods for solving challenging practical problems. This accessible book covers a majority of aspects of Bayesian methods and computations, including spatial statistics and computation using the dedicated R package bmstdr. With worked examples, numerical illustrations, and exercises, readers can build up their understanding of Bayesian methods without getting clouded in technicalities. The book also includes R code notes detailing the algorithms used to produce tables and figures, with data and code available via an online supplement. Practical examples of spatio-temporal modeling are discussed, including point-referenced and areal unit data. The emphasis is on validating models by splitting data into test and training sets, following the philosophy of machine learning and data science. This book aims to make spatio-temporal modeling and analysis accessible and understandable to a wide audience of students and researchers.

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