qgam: Bayesian Nonparametric Quantile Regression Modeling in R

qgam: Bayesian Nonparametric Quantile Regression Modeling in R

Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package. While the GAM methods provided by mgcv are based on the assumption that the response distribution is modeled parametric...

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Bibliographic Details
Main Authors: Matteo Fasiolo, Simon N. Wood, Margaux Zaffran, Raphaël Nedellec, Yannig Goude
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2021-11-01
Series:Journal of Statistical Software
Subjects:
bayesian quantile regression
generalized additive models
regression splines
calibrated bayes
fast bayesian inference
r
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/3800

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