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Regression quantiles with errors-in-variables

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In a lot of situations, variables are measured with errors. While this problem has been previously studied in the kontext of kernel regression, no work has been done in quantile regression. To estimate this function we use deconvoluting kernel estimators. The asymptotic behaviour of these estimators depends on the smoothness of the noise distribution.

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D. A. Ioannides, E. Matzner-Lober

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Adapt according to the presented license agreement and reference the original author.