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Section: New Results

QuantifQuantile: An R Package for Performing Quantile Regression Through Optimal Quantization

The following result has been obtained by J. Saracco (Inria CQFD) and I. Charlier (Inria CQFD), D. Paindaveine (ULB).

In this work, we describe an R package, called QuantifQuantile, that allows to perform quantization-based quantile regression. 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. We describe also the various functions of the package and provide examples.