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 2 months ago

11.02 score 16 stars 45 dependents 2.0k scripts 12k downloads

gamlss.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 21 hours ago

10.31 score 4 stars 67 dependents 338 scripts 12k downloads

gamlss.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 10 months ago

7.25 score 47 dependents 108 scripts 12k downloads

gamlss2 - 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 19 hours ago

6.27 score 7 stars 1 dependents 4 scripts

gamlss.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 1 months ago

5.64 score 2 stars 24 scripts 267 downloads

gamlss.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 10 months ago

4.98 score 1 dependents 63 scripts 705 downloads

gamlss.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 10 months ago

4.66 score 2 dependents 77 scripts 598 downloads

gamlss.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 261 downloads

gamlss.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 413 downloads

gamlss.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 251 downloads

gamlss.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 426 downloads