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qgam (2.0.0)

Published 2026-02-24 13:47:24 +00:00 by atheaadmin

Installation

Setup this registry in your Rprofile.site file:

options("repos" = c(getOption("repos"), c(gitea="")))

To install the package, run the following command:

install.packages("qgam")

For more information on the CRAN registry, see the documentation.

About this package

Smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2020) <doi:10.1080/01621459.2020.1725521>. See Fasiolo at al. (2021) <doi:10.18637/jss.v100.i09> for an introduction to the package. Differently from 'quantreg', the smoothing parameters are estimated automatically by marginal loss minimization, while the regression coefficients are estimated using either PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian credible intervals of the estimated effects have approximately the correct coverage. The main function is qgam() which is similar to gam() in 'mgcv', but fits non-parametric quantile regression models.Smooth Additive Quantile Regression Models

Dependencies

Imports	shiny, plyr, doParallel, parallel, grDevices
Depends	R (>= 4.0), mgcv (>= 1.9)
Suggests	knitr, rmarkdown, MASS, RhpcBLASctl, testthat

Details

CRAN

2026-02-24 13:47:24 +00:00

1

GPL (>= 2)

Matteo Fasiolo

Ben Griffiths

Simon N. Wood

Margaux Zaffran

Yannig Goude

Raphael Nedellec

3.9 MiB

Assets (1)

qgam_2.0.0.tar.gz 3.9 MiB

Versions (1) View all

2.0.0 2026-02-24