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Handbook of Spatial Statistics (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) - Tapa dura

Libro 2 de 27: Chapman & Hall/CRC Handbooks of Modern Statistical Methods
 
9781420072877: Handbook of Spatial Statistics (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

Sinopsis

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters.

The handbook begins with a historical introduction detailing the evolution of the field. It then focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and spatial point patterns. The book also contains a section on space–time work as well as a section on important topics that build upon earlier chapters.

By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.

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Acerca del autor

Alan E. Gelfand, Department of Statistical Science, Duke University, Durham, North Carolina, USA

Peter J. Diggle, School of Health and Medicine, Lancaster University, UK

Montserrat Fuentes, Department of Statistics, North Carolina State University, Raleigh, USA

Peter Guttorp, Department of Statistics, University of Washington, Seattle, USA, and Norwegian Computing Center, Oslo, Norway

De la contraportada

Based on the work of prominent researchers, this handbook provides broad, thorough coverage of this vibrant area, from historical to contemporary topics. It explores the modeling advances, computational approaches, and methodology that have emerged in recent years. The book focuses on continuous and discrete spatial variation, spatial point patterns, and spatio-temporal processes. It also covers multivariate spatial process models, spatial aggregation, spatial misalignment, and spatial gradients in depth. The theory and applications are illustrated with many real-world data examples.

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