Assessing model adequacy in possibly misspecified quantile regression

Hohsuk Noh, Anouar El Ghouch and Ingrid Van Keilegom ()

Computational Statistics & Data Analysis, 2013, vol. 57, issue 1, 558-569

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.

Keywords: Coefficient of determination; Conditional quantiles; Lack-of-fit; Linear model; Prediction quality (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:57:y:2013:i:1:p:558-569

DOI: 10.1016/j.csda.2012.07.020

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