Interface for extra high-dimensional smooth functions for Generalized Additive Models for Location Scale and Shape (GAMLSS) including (adaptive) lasso, ridge, elastic net and least angle regression.

A GAMLSS add on package for fitting mixtute distributions
The main purpose of this package is to allow fitting of mixture distributions with GAMLSS models.
GPL (version 2 or later) See file LICENCE

A GAMLSS add on package for fitting mixture distributions

The main purpose of this package is to allow fitting of
mixture distributions with GAMLSS models.

A GAMLSS Add-on Package For Fitting Mixture Distributions

Fitting Mixture Distributions with GAMLSS
R (>= 2.2.1), gamlss.dist, gamlss, nnet, stats, graphics

The main purpose of this package is to allow fitting of
mixture distributions with generalised additive models for location
scale and shape models see Chapter 7 of Stasinopoulos et al. (2017) <doi:10.1201/b21973-4>.

A GAMLSS add on package for fitting non linear parametric models
Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>, Bob Rigby <r.rigby@londonmet.ac.uk> with
contributions from Philippe Lambert.
The main purpose of this package is to allow one extra method for fitting
GAMLSS models. The main function nlgamlss() can fit any parametric
(up to four parameter) GAMLSS distribution.

Fitting non linear parametric GAMLSS models
This is an add on package to GAMLSS. It allows one extra method for fitting
GAMLSS models. The main function nlgamlss() can fit any parametric
(up to four parameter) GAMLSS distribution.

Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>, Bob
Rigby <r.rigby@londonmet.ac.uk> with contributions from
Philippe Lambert.
This is an add on package to GAMLSS. It allows one extra
method for fitting GAMLSS models. The main function nlgamlss()
can fit any parametric (up to four parameter) GAMLSS
distribution.

Fernanda De Bastiani, Mikis Stasinopoulos,

R (>= 2.15.0), gamlss.dist, gamlss (>= 4.2-7), spam, mgcv

c(person("Fernanda", "De Bastiani", role = c("aut", "cre", "cph"), email = "fernandadebastiani@gmail.com"),
person("Mikis", "Stasinopoulos", role = c("aut"),
email = "d.stasinopoulos@londonmet.ac.uk"),
person("Bob", "Rigby", role = c("aut"),
email = "r.rigby@londonmet.ac.uk" )
)
It allows us to fit Gaussian Markov Random Field (GMRF) within the GAMLSS algorithms.
Fernanda De Bastiani [aut, cre, cph],
Mikis Stasinopoulos [aut],
Bob Rigby [aut]