"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.
This entry introduces some key principles around spatial data (i.e., mappable data) in the social sciences and geostatistical methods for their analysis.
With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto ...
This text will also prove to be a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.
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xiv List of Contributors Ramón Giraldo National University of Colombia Department of Statistics Colombia Dae-Jin Lee BCAM–Basque Center for Applied Mathematics Spain Alberto Guadagnini Politecnico di Milano Department of Civil and ...
The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.
Written to be accessible to the nonspecialist, this volume surveys the applications of spatial statistics to a wide range of areas, including image analysis, geosciences, physical chemistry, and ecology.
This book presents an introduction to geostatistics stressing the multivariate aspects for scientists, engineers or statisticians.
This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain.