title: T-type Corrected-Loss Estimation for Error-in-Variable Model.
abstract: In this paper, we consider a linear model in which the covariates are measured with errors. We propose a t-type corrected-loss estimation of the covariate effect, when the measurement error follows the Laplace distribution. The proposed estimator is asymptotically normal. In practical studies, some outliers that diminish the robustness of the estimation occur. Simulation studies show that the estimators are resistent to vertical outliers and an application of Six-Minute Walk test is presented to show that the proposed method performs well.
authors.affiliation: School of Mathematical Sciences, Beijing Normal University, Beijing, PR China.
authors.forename: Jiao
authors.initials: J
authors.lastname: Jin
authors.affiliation: Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA.
authors.forename: Liang
authors.initials: L
authors.lastname: Zhu
authors.affiliation: School of Mathematical Sciences, Beijing Normal University, Beijing, PR China.
authors.forename: Xingwei
authors.initials: X
authors.lastname: Tong
authors.affiliation: Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA.
authors.forename: Kirsten K
authors.initials: KK
authors.lastname: Ness
keywords: Corrected-loss estimation; Error-in-variable model; Robust analysis; T-type