QuantifQuantile : an R package for performing quantile regression through optimal quantization

Abstract : In quantile regression, various quantiles of a response variable Y are modelled as func- tions of covariates (rather than its mean). An important application is the construction of reference curves/surfaces and conditional prediction intervals for Y. Recently, a nonparametric quantile regression method based on the concept of optimal quantization was proposed. This method competes very well with k-nearest neighbor, kernel, and spline methods. In this paper, we describe an R package, called QuantifQuantile, that allows to perform quantization-based quantile regression. We describe the various functions of the package and provide examples.
Type de document :
Article dans une revue
The R Journal, R Foundation for Statistical Computing, 2015
Liste complète des métadonnées

Littérature citée [20 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01108505
Contributeur : Isabelle Charlier <>
Soumis le : mercredi 13 janvier 2016 - 18:06:07
Dernière modification le : jeudi 11 janvier 2018 - 06:22:11
Document(s) archivé(s) le : vendredi 11 novembre 2016 - 04:59:29

Fichier

revison_Rjournal.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01108505, version 2

Collections

Citation

Isabelle Charlier, Davy Paindaveine, Jérôme Saracco. QuantifQuantile : an R package for performing quantile regression through optimal quantization. The R Journal, R Foundation for Statistical Computing, 2015. 〈hal-01108505v2〉

Partager

Métriques

Consultations de la notice

260

Téléchargements de fichiers

116