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gamboostLSS implements boosting algorithms for fitting generalized linear, additive and interaction models for to potentially high-dimensional data. Instead of modeling only the mean, gamboostLSS enables the user to model various distribution parameters such as location, scale and shape at the same time (hence the name GAMLSS, generalized additive models for location, scale and shape).

Using gamboostLSS

Issues & Feature Requests

For issues, bugs, feature requests etc. please use the GitHub Issues.


To be able to use the install_github() command, one needs to install devtools first: install.packages("devtools")