Abstract
Quantile regression can be used to obtain a nonparametric estimateof a conditional quantile function. The presence of quantile crossing, however,leads to an invalid distribution of the response and makes it dicult to use thetted model for prediction. In this work, we show that crossing can be alleviatedor completely eliminated by explicit modeling of the regression coecients as afunction of the percentile values in (0,1). We illustrate the approach via a wellknowndataset by emphasizing dierences with respect to the competitors.
Lingua originale | English |
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Titolo della pubblicazione ospite | Proceedings of the 34th International Workshop on Statistical Modelling |
Pagine | 301-305 |
Numero di pagine | 5 |
Stato di pubblicazione | Published - 2019 |