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Consistency of nonlinear regression quantiles under Type I censoring weak dependence and general covariate design

URN to cite this document:
urn:nbn:de:bvb:355-opus-4804
Oberhofer, Walter ; Haupt, Harry
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Date of publication of this fulltext: 11 Mar 2005 13:47


Abstract

For both deterministic or stochastic regressors, as well as parametric nonlinear or linear regression functions, we prove the weak consistency of the coefficient estimators for the Type I censored quantile regression model under different censoring mechanisms with censoring points depending on the observation index (in a nonstochastic manner) and a weakly dependent error process. Our ...

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