gamlss2: Infrastructure for Flexible Distributional Regression
Installation
The development version of gamlss2 can be installed via
install.packages("gamlss2",
repos = c("https://gamlss-dev.R-universe.dev", "https://cloud.R-project.org"))
Overview
The primary purpose of this package is to facilitate the creation of advanced infrastructures designed to enhance the GAMLSS modeling framework. Notably, the gamlss2
package represents a significant overhaul of its predecessor, gamlss
, with a key emphasis on improving estimation speed and incorporating more flexible infrastructures. These enhancements enable the seamless integration of various algorithms into GAMLSS, including gradient boosting, Bayesian estimation, regression trees, and forests, fostering a more versatile and powerful modeling environment.
Moreover, the package expands its compatibility by supporting all model terms from the base R mgcv
package. Additionally, the gamlss2
package introduces the capability to accommodate more than four parameter families. Essentially, this means that users can now specify any type of model using these new infrastructures, making the package highly flexible and accommodating to a wide range of modeling requirements.
- The main model function is
gamlss2()
. - The default optimizer functions is
RS()
. Optimizer functions can be exchanged. - Most important methods:
summary()
,plot()
,predict()
. - Easy development of new family objects, see
?family.gamlss2
. - User-specific “special” terms are possible, see
?special_terms
.
For examples, please visit the manual pages.
help(package = "gamlss2")