• Corpus ID: 220381015

qgam: Bayesian non-parametric quantile regression modelling in R

  title={qgam: Bayesian non-parametric quantile regression modelling in R},
  author={Matteo Fasiolo and Simon N. Wood and Margaux Zaffran and Raphael Nedellec and Yannig Goude},
  journal={arXiv: Methodology},
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 modelled parametrically, here we discuss more flexible methods that do not entail any parametric assumption. In particular, this article introduces the qgam package, which is an extension of mgcv providing fast… 
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