Name: Statistical Methods for Spatial Data Analysis (Chapman & Hall (en Inglés)
Price: 176930.00 CLP
Availability: InStock
Author: Oliver Schabenberger; Carol A. Gotway
ISBN: 9781584883227

portada Statistical Methods for Spatial Data Analysis (Chapman & Hall (en Inglés)

Formato

Libro Físico

Editorial

Chapman & Hall

Autor

Oliver Schabenberger; Carol A. Gotway

Año

2004

Idioma

Inglés

N° páginas

512

Encuadernación

Tapa Dura

Peso

ISBN

1584883227

ISBN13

9781584883227

N° edición

Categorías

Probabilidad y estadística

Statistical Methods for Spatial Data Analysis (Chapman & Hall (en Inglés)

Oliver Schabenberger; Carol A. Gotway (Autor) · Chapman & Hall · Tapa Dura

Libro Físico

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Reseña del libro "Statistical Methods for Spatial Data Analysis (Chapman & Hall (en Inglés)"

Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. 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. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes.Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.