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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/18164


    Title: On Robust Linear Regression with Incomplete Data
    Authors: Atkinson, Anthony C.;鄭宗記
    Atkinson, Anthony C.;Cheng, Tsung-Chi
    Keywords: EM algorithm;Forward search algorithm;High breakdown point;Least trimmed squares;Missing values;Multiple imputation;Regression diagnostics;Stalactite plot
    Date: 2000-06
    Issue Date: 2008-12-19 14:52:10 (UTC+8)
    Abstract: In this paper, we use recently developed methods of very robust regression to extend missing value techniques to data with several outliers. Simulation experiments reveal that additional outliers may be imputed if one ignores the outliers already in the data. The combination of the forward search algorithm for high breakdown point estimators and the EM algorithm or multiple imputation for missing values can avoid problems of this kind. Some multiple deletion diagnostics for linear regression with incomplete data are also discussed.
    Relation: Computational Statistics and Data Analysis 33(4),361-380
    Data Type: article
    Appears in Collections:[Department of Statistics] Periodical Articles

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