Authors: Belomestny, Denis
Klochkov, Egor
Spokoiny, Vladimir
Title: Sieve maximum likelihood estimation in a semi-parametric regression model with errors in variables
Language (ISO): en
Abstract: The paper deals with a semi-parametric regression problem under deterministic and regular design which is observed with errors. We first linearise the problem using a sieve approach and then apply the total penalised maximum likelihood estimator to the linearised model. Sufficient conditions for √n-consistency and efficiency under parametric assumption are derived and a possible misspecification bias under different smoothness assumptions on the design is analysed. The Monte Carlo simulations show the performance of the estimator with simulated data.
Subject Headings: errors-in-variables model
√n-consistency
regression
URI: http://hdl.handle.net/2003/34888
http://dx.doi.org/10.17877/DE290R-16936
Issue Date: 2016
Appears in Collections:Sonderforschungsbereich (SFB) 823

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