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