Statistics, Department of

The R Journal
Date of this Version
12-2015
Document Type
Article
Citation
The R Journal (December 2015) 7(2); Editor: Bettina Grün
Abstract
In quantile regression, various quantiles of a response variable Y are modelled as functions 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.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2015, The R Foundation. Open access material. License: CC BY 3.0 Unported