Spatial Statistics and Modeling Spatial Statistics and Modeling
Springer Series in Statistics

Spatial Statistics and Modeling

    • ‏139٫99 US$
    • ‏139٫99 US$

وصف الناشر

Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. 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-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete.

 The most important statistical methods and their asymptotic  properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation).
A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in  probability and mathematical statistics is assumed,  three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background  and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference.

This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI).

Carlo Gaetan is Associate Professor of Statistics in the Department of Statistics at the Ca' Foscari University of Venice.

Xavier Guyon is Professor  Emeritus at the University of Paris 1 Panthéon-Sorbonne. He is author of a Springer monograph on random fields.

النوع
علم وطبيعة
تاريخ النشر
٢٠٠٩
١٠ نوفمبر
اللغة
EN
الإنجليزية
عدد الصفحات
٣١٦
الناشر
Springer New York
البائع
Springer Nature B.V.
الحجم
٦٫١
‫م.ب.‬
Advanced Linear Modeling Advanced Linear Modeling
٢٠١٩
Gaussian Markov Random Fields Gaussian Markov Random Fields
٢٠٠٥
Introduction to Functional Data Analysis Introduction to Functional Data Analysis
٢٠١٧
An Introduction to Bayesian Inference, Methods and Computation An Introduction to Bayesian Inference, Methods and Computation
٢٠٢١
Advances on Theoretical and Methodological Aspects of Probability and Statistics Advances on Theoretical and Methodological Aspects of Probability and Statistics
٢٠١٩
Advances in Directional and Linear Statistics Advances in Directional and Linear Statistics
٢٠١٠
The Elements of Statistical Learning The Elements of Statistical Learning
٢٠٠٩
Regression Modeling Strategies Regression Modeling Strategies
٢٠١٥
Forecasting with Exponential Smoothing Forecasting with Exponential Smoothing
٢٠٠٨
An Introduction to Sequential Monte Carlo An Introduction to Sequential Monte Carlo
٢٠٢٠
Simulation and Inference for Stochastic Differential Equations Simulation and Inference for Stochastic Differential Equations
٢٠٠٩
Permutation, Parametric, and Bootstrap Tests of Hypotheses Permutation, Parametric, and Bootstrap Tests of Hypotheses
٢٠٠٦