gamlss - Generalized Additive Models for Location Scale and Shape
Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.
Last updated 4 months ago
11.23 score 16 stars 49 dependents 2.0k scripts 18k downloadsgamlss.dist - Distributions for Generalized Additive Models for Location Scale and Shape
A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a 'log' or a 'logit' transformation respectively.
Last updated 11 days ago
10.50 score 4 stars 71 dependents 346 scripts 15k downloadsgamlss.data - Data for Generalized Additive Models for Location Scale and Shape
Data used as examples in the books on Generalized Additive Models for Location Scale and Shape: Stasinopoulos, Rigby, Heller, Voudouris, De Bastiani (2017). Flexible Regression and Smoothing: Using GAMLSS in R, <doi:10.1201/b21973>. Rigby, Stasinopoulos, Heller, De Bastiani (2019). Distributions for Modeling Location, Scale, and Shape Using GAMLSS in R, <doi:10.1201/9780429298547>. Stasinopoulos, Kneib, Klein, Mayr, Heller (2024). Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications, <doi:10.1017/9781009410076>.
Last updated 12 months ago
7.34 score 50 dependents 108 scripts 14k downloadsgamlss.ggplots - Plotting Functions for Generalized Additive Model for Location Scale and Shape
Functions for plotting Generalized Additive Models for Location Scale and Shape from the 'gamlss' package, Stasinopoulos and Rigby (2007) <doi:10.18637/jss.v023.i07>, using the graphical methods from 'ggplot2'.
Last updated 3 months ago
5.58 score 2 stars 24 scripts 338 downloadsgamlss2 - GAMLSS Infrastructure for Flexible Distributional Regression
Next generation infrastructure for generalized additive models for location, scale, and shape (GAMLSS) and distributional regression more generally. The package provides a fresh reimplementaton of the classic 'gamlss' package while being more modular and facilitating the creation of advanced terms and models.
Last updated 9 days ago
5.23 score 7 stars 1 dependents 4 scriptsgamlss.add - Extra Additive Terms for Generalized Additive Models for Location Scale and Shape
Interface for extra smooth functions including tensor products, neural networks and decision trees.
Last updated 12 months ago
4.98 score 1 dependents 64 scripts 733 downloadsgamlss.tr - Generating and Fitting Truncated 'gamlss.family' Distributions
This is an add-on package to 'gamlss' which supports truncated distributions in Generalized Additive Models for Location Scale and Shape. The main function gen.trun() generates truncated version of an existing gamlss family distribution.
Last updated 11 months ago
4.66 score 2 dependents 77 scripts 982 downloadsgamlss.spatial - Spatial Terms in Generalized Additive Models for Location Scale and Shape
The packages enables fitting Gaussian Markov Random Fields within the Generalized Additive Models for Location Scale and Shape algorithms.
Last updated 1 years ago
3.74 score 11 scripts 357 downloadsgamlss.cens - Fitting an Interval Response Variable Using `gamlss.family' Distributions
This is an add-on package to GAMLSS. The purpose of this package is to allow users to fit interval response variables in GAMLSS models. The main function gen.cens() generates a censored version of an existing GAMLSS family distribution.
Last updated 1 years ago
3.68 score 1 dependents 32 scripts 843 downloadsgamlss.foreach - Parallel Computations for Distributional Regression
Computationally intensive calculations for Generalized Additive Models for Location Scale and Shape, <doi:10.1111/j.1467-9876.2005.00510.x>.
Last updated 1 years ago
3.26 score 1 dependents 12 scripts 311 downloadsgamlss.mx - Fitting Mixture Distributions with Generalized Additive Models for Location Scale and Shape
The package provides fitting of mixture distributions with Generalized Additive Models for Location Scale and Shape, see Chapter 7 of Stasinopoulos et al. (2017) <doi:10.1201/b21973-7>.
Last updated 1 years ago
3.08 score 1 stars 24 scripts 673 downloads