Belomestny, DenisKlochkov, EgorSpokoiny, Vladimir2016-04-122016-04-122016http://hdl.handle.net/2003/3488810.17877/DE290R-16936The 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.enDiscussion Paper / SFB823;15, 2016errors-in-variables model√n-consistencyregression310330620working paper