Jorge Mateu & Werner G. Müller 
Spatio-temporal Design [EPUB ebook] 
Advances in Efficient Data Acquisition

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.

Spatio-temporal Design presents an excellent book for
graduate level students as well as a valuable reference for
researchers and practitioners in the fields of applied mathematics,
engineering, and the environmental and health sciences.

Giới thiệu về tác giả

Jorge Mateu, Department of Mathematics of the University Jaume I of Castellon, Spain,

Werner G. Müller, Department of Applied Statistics, Johannes Kepler University Linz, Austria.