The R Journal: article published in 2013, volume 5:2

spMC: Modelling Spatial Random Fields with Continuous Lag Markov Chains
Luca Sartore , The R Journal (2013) 5:2, pages 16-28.

Abstract Currently, a part of the R statistical software is developed in order to deal with spatial models. More specifically, some available packages allow the user to analyse categorical spatial random patterns. However, only the spMC package considers a viewpoint based on transition probabilities between locations. Through the use of this package it is possible to analyse the spatial variability of data, make inference, predict and simulate the categorical classes in unobserved sites. An example is presented by analysing the well-known Swiss Jura data set.

Received: 2012-08-27; online 2013-09-27
CRAN packages: spMC, gstat, geoRglm, RandomFields
CRAN Task Views implied by cited CRAN packages: Spatial, SpatioTemporal, Bayesian

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2013-022,
  author = {Luca Sartore},
  title = {{spMC: Modelling Spatial Random Fields with Continuous Lag
          Markov Chains}},
  year = {2013},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2013-022},
  url = {https://doi.org/10.32614/RJ-2013-022},
  pages = {16--28},
  volume = {5},
  number = {2}
}