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http://dx.doi.org/10.7465/jkdi.2014.25.2.439

Quantile regression with errors in variables  

Shim, Jooyong (Department of Data Science, Inje University)
Publication Information
Journal of the Korean Data and Information Science Society / v.25, no.2, 2014 , pp. 439-446 More about this Journal
Abstract
Quantile regression models with errors in variables have received a great deal of attention in the social and natural sciences. Some eorts have been devoted to develop eective estimation methods for such quantile regression models. In this paper we propose an orthogonal distance quantile regression model that eectively considers the errors on both input and response variables. The performance of the proposed method is evaluated through simulation studies.
Keywords
Check function; errors in variables; iteratively reweighted least squares procedure; orthogonal distance regression; quantile regression;
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Times Cited By KSCI : 3  (Citation Analysis)
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