155 citations · 188 across the 3 of their papers we have counts for
3 papers
qgam: Bayesian non-parametric quantile regression modelling in R
Matteo Fasiolo, Simon N. Wood, Margaux Zaffran +2
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.…
Scalable visualisation methods for modern Generalized Additive Models
Matteo Fasiolo, Raphaël Nedellec, Yannig Goude +1
In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applicatio…
Fast calibrated additive quantile regression
M. Fasiolo, S. N. Wood, M. Zaffran +2
We propose a novel framework for fitting additive quantile regression models, which provides well calibrated inference about the conditional quantiles and fast automatic estimation…