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Spatio-Temporal Statistics with R

List Price: $72.99
SKU:
9781138711136
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  • Product Details

    Author:
    Christopher K. Wikle, Andrew Zammit-Mangion, Noel Cressie
    Format:
    Hardcover
    Pages:
    396
    Publisher:
    CRC Press (February 18, 2019)
    Language:
    English
    Audience:
    Professional and scholarly
    ISBN-13:
    9781138711136
    Weight:
    36.75oz
    Dimensions:
    7" x 10"
    File:
    TAYLORFRANCIS-TayFran_260409051851155-20260409.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $72.99
    Country of Origin:
    United States
    Series:
    Chapman & Hall/CRC The R Series
    Case Pack:
    14
    As low as:
    $69.34
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Pub Discount:
    30
    Imprint:
    Chapman and Hall/CRC
  • Overview

    The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps.

    Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book:

    • Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation
    • Provides a gradual entry to the methodological aspects of spatio-temporal statistics
    • Provides broad coverage of using R as well as "R Tips" throughout.
    • Features detailed examples and applications in end-of-chapter Labs
    • Features "Technical Notes" throughout to provide additional technical detail where relevant
    • Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more

    The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.