gamlss.spatial-package: Spatial Terms in Generalized Additive Models for Location...

In gamlss.spatial: Spatial Terms in Generalized Additive Models for Location Scale and Shape Models

Spatial Terms in Generalized Additive Models for Location Scale and Shape Models

Description

It allows us to fit Gaussian Markov Random Field within the Generalized Additive Models for Location Scale and Shape algorithms.

Details

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Author(s)

Fernanda De Bastiani [aut, cre, cph], Mikis Stasinopoulos [aut], Robert Rigby [aut]

Maintainer: Fernanda De Bastiani <[e-mail]>

References

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/).

Examples

library(mgcv)
data(columb)
data(columb.polys)
m1 <- MRFA(columb$crime, columb$district, polys=columb.polys)
draw.polys(columb.polys, m1) 

gamlss.spatial documentation built on Oct. 15, 2023, 5:06 p.m.