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Mingxing Zhang
Zixin Liu

Author(s) and WSEAS

Mingxing Zhang
Zixin Liu

WSEAS Transactions on Systems

Print ISSN: 1109-2777
E-ISSN: 2224-2678

Volume 17, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 17, 2018

Kriging Regression Imputation Method to Semiparametric Model with Missing Data

AUTHORS: Mingxing Zhang, Zixin Liu

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ABSTRACT: This paper investigates a class of estimation problems of the semiparametric model with missing data. In order to overcome the robust defect of traditional complete data estimation method and regression imputation estimation technique, we propose a modified imputation estimation approach called Kriging-regression imputation. Compared with previous method used in the references cited therein , the new proposed method not only makes more use of the data information, but also has better robustness. Model estimation and asymptotic distribution of the estimators are also derived theoretically. In order to improve the robustness, LASSO technique is further introduced into Kriging-regression imputation. Numerical experiment is also provided to show the effectiveness and superiority of our method.

KEYWORDS: semiparameter model, data missing, imputation techniques, asymptotic normality, consistency


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WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 17, 2018, Art. #19, pp. 178-190

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