Spatio-Temporal Statistics With R.

spacetime: Spatio-Temporal Data in R

This document describes classes and methods designed to deal with different types of spatio-temporal data in R implemented in the R package spacetime, and provides examples for analyzing them. It builds upon the classes and methods for spatial data from package sp, and for time series data from package xts. The goal is to cover a number of useful representations for spatio-temporal sensor data,...

spTimer: Spatio-Temporal Bayesian Modeling Using R

Hierarchical Bayesian modeling of large point referenced space-time data are increasingly becoming feasible in many environmental applications due to the recent advances in both statistical methodology and computation power. Implementation of these methods using the Markov chain Monte Carlo (MCMC) computational techniques, however, requires development of problem specific and user written compu...

Spatial and spatio-temporal models with R-INLA.

During the last three decades, Bayesian methods have developed greatly in the field of epidemiology. Their main challenge focusses around computation, but the advent of Markov Chain Monte Carlo methods (MCMC) and in particular of the WinBUGS software has opened the doors of Bayesian modelling to the wide research community. However model complexity and database dimension still remain a constrai...

Modern perspectives on statistics for spatio-temporal data

Spatio-temporal statisticalmodels are increasingly beingused across awide variety of scientific disciplines to describe and predict spatially explicit processes that evolve over time. Although descriptivemodels that approach this problem from the second-order (covariance) perspective are important, many real-world processes are dynamic, and it can bemore efficient in such cases to characterize ...

Spatio-temporal statistics: applications in epidemiology, veterinary medicine and ecology.