Multivariate partially linear regression in the presence of measurement error

  • Seçil Yalaz
Original Paper


In this paper, multivariate partially linear model with error in the explanatory variable of nonparametric part, where the response variable is m dimensional, is considered. By modification of local-likelihood method, an estimator of parametric part is driven. Moreover, the asymptotic normality of the generalized least square estimator of the parametric component is investigated when the error distribution function is either ordinarily smooth or super smooth. Applications in the Engel curves are discussed and through Monte Carlo experiments performances of \(\hat{\beta }_{n}\) are investigated.


Multivariate regression Partially linear models Errors in variables Kernel smoothing Asymptotic normality 


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mathematics, Faculty of ScienceDicle UniversitySurTurkey

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