Kernel estimator and predictor of partially linear mixed-effect errors-in-variables model
[ X ]
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper considers the partially linear mixed-effect model relating a response Y to predictors (X, Z, T) with mean function X-T beta + Z(T)b + g(T) which is a combination of the linear mixed-effect model and the nonparametric smooth function. The proposed model contains an additive measurement error in X. Taavoni and Arashi (Kernel estimation in semiparametric mixed-effect longitudinal modelling. Statist Papers. 2019. Available from: https://doi.org/10.1007/s00362019-01125-8.) approximated the nonparametric function by the profile kernel method, and made use of the weighted least squares to estimate the regression coefficients when measurement error was ignored. We derive a simple modification of their estimators by correction for attenuation stems from measurement error and demonstrate that the linear parts estimator is asymptotically normal.
Açıklama
Anahtar Kelimeler
Errors In Variables, Partially Linear Model, Partially Linear Mixed-Effects Model, Kernel Regression, Asymptotic Normality
Kaynak
Journal of Statistical Computation and Simulation
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
91
Sayı
5
