Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10327542 | Computational Statistics & Data Analysis | 2013 | 12 Pages |
Abstract
Possibly misspecified linear quantile regression models are considered. A measure for assessing the combined effect of several covariates on a certain conditional quantile function is proposed. The measure is based on an adaptation to quantile regression of the famous coefficient of determination originally proposed for mean regression, and compares a 'reduced' model to a 'full' model, both of which can be misspecified. An estimator of this measure is proposed and its asymptotic distribution is investigated both in the non-degenerate and the degenerate case. The finite sample performance of the estimator is studied through a number of simulation experiments. The proposed measure is also applied to a data set on body fat measures.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Hohsuk Noh, Anouar El Ghouch, Ingrid Van Keilegom,