gamlss.spatial-package {gamlss.spatial} | R Documentation |
It allows us to fit Gaussian Markov Random Field within the Generalized Additive Models for Location Scale and Shape algorithms.
The DESCRIPTION file:
Package: | gamlss.spatial |
Type: | Package |
Title: | Spatial Terms in Generalized Additive Models for Location Scale and Shape Models |
Version: | 3.0-2 |
Date: | 2023-10-14 |
Authors@R: | c(person("Fernanda", "De Bastiani", role = c("aut", "cre", "cph"), email = "fernandadebastiani@gmail.com"), person("Mikis", "Stasinopoulos", role = c("aut"), email = "d.stasinopoulos@gre.ac.uk"), person("Robert", "Rigby", role = c("aut")) ) |
Description: | It allows us to fit Gaussian Markov Random Field within the Generalized Additive Models for Location Scale and Shape algorithms. |
License: | GPL-2 | GPL-3 |
URL: | https://www.gamlss.com/ |
Depends: | R (>= 2.15.0), gamlss.dist, gamlss (>= 4.2-7), gamlss.add, spam, mgcv |
Imports: | stats, grDevices, graphics, methods |
Repository: | CRAN |
NeedsCompilation: | no |
Packaged: | 2015-07-09 13:32:17 UTC; stasinom |
Author: | Fernanda De Bastiani [aut, cre, cph], Mikis Stasinopoulos [aut], Robert Rigby [aut] |
Maintainer: | Fernanda De Bastiani <fernandadebastiani@gmail.com> |
RoxygenNote: | 5.0.1 |
Index of help topics:
MRF Markov Random Fields Fitting Functions draw.polys Additional supporting functions for random Markov fields gamlss.gmrf Gaussian Markov Random Field fitting within GAMLSS gamlss.spatial-package Spatial Terms in Generalized Additive Models for Location Scale and Shape Models
Fernanda De Bastiani [aut, cre, cph], Mikis Stasinopoulos [aut], Robert Rigby [aut]
Maintainer: Fernanda De Bastiani <fernandadebastiani@gmail.com>
De Bastiani, F. Rigby, R. A., Stasinopoulos, D. M., Cysneiros, A. H. M. A. and Uribe-Opazo, M. A. (2016) Gaussian Markov random spatial models in GAMLSS. Journal of Applied Statistics, pp 1-19.
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.
Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.
Rue and Held (2005) Gaussian markov random fields: theory and applications, Chapman & Hall, USA.
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.
(see also https://www.gamlss.com/).
library(mgcv)
data(columb)
data(columb.polys)
m1 <- MRFA(columb$crime, columb$district, polys=columb.polys)
draw.polys(columb.polys, m1)