Package: qgam
Type: Package
Title: Smooth Additive Quantile Regression Models
Version: 1.1.1
Date: 2017-8-29
Author: Matteo Fasiolo, Simon N. Wood, Yannig Goude, Raphael Nedellec.
Maintainer: Matteo Fasiolo <matteo.fasiolo@gmail.com>
Description: Smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2017) <arXiv:1707.03307>. 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.
License: GPL (>= 2)
Depends: mgcv (>= 1.8.18)
Imports: shiny, plyr, doParallel, parallel, grDevices
Suggests: knitr, MASS, RhpcBLASctl
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-08-29 10:49:44 UTC; teo
Repository: CRAN
Date/Publication: 2017-08-29 12:15:16 UTC
