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Spatio-temporal Design: Advances in Efficient Data Acquisition Hardback - 2012 - 1st Edition
by JORGE MATEU
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Details
- Title Spatio-temporal Design: Advances in Efficient Data Acquisition
- Author JORGE MATEU
- Binding Hardback
- Edition number 1st
- Edition 1
- Condition New
- Pages 349
- Language ENG
- Publisher Wiley, West Sussex, United Kingdom
- Publication date 2012-12
- Features Bibliography, Illustrated, Index
- Bookseller's Inventory # 9093684
- ISBN 9780470974292
-
Themes
- Aspects (Academic): Science/Technology Aspects
- Quantity available 1
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From the publisher
From the rear cover
A state-of-the-art presentation of optimum spatio-temporal sampling design - bridging classic ideas with modern statistical modeling concepts and the latest computational methods.
Spatio-temporal Design presents a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition. A common problem set is interwoven throughout the chapters, providing various perspectives to illustrate a complete insight to the problem at hand.
Motivated by the high demand for statistical analysis of data that takes spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to discuss optimum spatio-temporal sampling design.
Spatio-temporal Design: Advances in Efficient Data Acquisition
- Provides an up-to-date account of how to collect space-time data for monitoring, with a focus on statistical aspects and the latest computational methods
- Discusses basic methods and distinguishes between design and model-based approaches to collecting space-time data.
- Features model-based frequentist design for univariate and multivariate geostatistics, and second-phase spatial sampling.
- Integrates common data examples and case studies throughout the book in order to demonstrate the different approaches and their integration.
- Includes real data sets, data generating mechanisms and simulation scenarios.
- Accompanied by a supporting website featuring R code.
