Regression quantiles with errors-in-variables
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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