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Complete Subset Averaging for Quantile Regressions
Preprint

Complete Subset Averaging for Quantile Regressions

Abstract

We propose a novel conditional quantile prediction method based on the complete subset averaging (CSA) for quantile regressions. All models under consideration are potentially misspecified and the dimension of regressors goes to infinity as the sample size increases. Since we average over the complete subsets, the number of models is much larger than the usual model averaging method which adopts sophisticated weighting schemes. We propose to …

Authors

Lee JH; Shin Y

Publication date

January 1, 2020

DOI

10.2139/ssrn.3551560

Preprint server

SSRN Electronic Journal