<b><i>Spatial and Spatio-Temporal Bayesian Models with R-INLA</i></b> provides a much needed, practically oriented <i>&</i> innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus o
Spatial and Spatio-Temporal Geostatistical Modeling and Kriging
✍ Scribed by José-MarÃa Montero, Gema Fernández-Avilés, Jorge Mateu
- Publisher
- Wiley
- Year
- 2015
- Tongue
- English
- Leaves
- 413
- Series
- Wiley Series in Probability and Statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R.
This book includes:
- Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods.
- The most innovative developments in the different steps of the kriging process.
- An up-to-date account of strategies for dealing with data evolving in space and time.
- An accompanying website featuring R code and examples
✦ Subjects
Горно-геологическая отрасль;Матметоды и моделирование в геологии;Геостатистика;
📜 SIMILAR VOLUMES
<b><i>Spatial and Spatio-Temporal Bayesian Models with R-INLA</i></b> provides a much needed, practically oriented <i>&</i> innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus o
"The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes
<p><p>Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users. STN modeling and computat
This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.<br />Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to