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qgam  

Smooth Additive Quantile Regression Models
View on CRAN: Click here


Download and install qgam package within the R console
Install from CRAN:
install.packages("qgam")

Install from Github:
library("remotes")
install_github("cran/qgam")

Install by package version:
library("remotes")
install_version("qgam", "1.3.4")



Attach the package and use:
library("qgam")
Maintained by
Matteo Fasiolo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-08-29
Latest Update: 2021-11-22
Description:
Smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2020) . See Fasiolo at al. (2021) 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.
How to cite:
Matteo Fasiolo (2017). qgam: Smooth Additive Quantile Regression Models. R package version 1.3.4, https://cran.r-project.org/web/packages/qgam
Previous versions and publish date:
1.1.1 (2017-08-29 14:15), 1.2.1 (2018-05-27 21:13), 1.2.2 (2018-05-29 00:23), 1.2.3 (2019-01-24 14:00), 1.3.0 (2019-06-07 11:50), 1.3.1 (2020-02-01 21:40), 1.3.2 (2020-02-03 20:40), 1.3.3 (2021-04-27 17:50)
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