政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/71197
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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/71197


    Title: Computing Least Trimmed Squares Regression with the Forward Search
    Authors: Atkinson A.C;鄭宗記
    Cheng,Tsung-Chi
    Contributors: 統計系
    Date: 1999.11
    Issue Date: 2014-11-06 18:23:10 (UTC+8)
    Abstract: Least trimmed squares (LTS) provides a parametric family of high breakdown estimators in regression with better asymptotic properties than least median of squares (LMS) estimators. We adapt the forward search algorithm of Atkinson (1994) to LTS and provide methods for determining the amount of data to be trimmed. We examine the efficiency of different trimming proportions by simulation and demonstrate the increasing efficiency of parameter estimation as larger proportions of data are fitted using the LTS criterion. Some standard data examples are analysed. One shows that LTS provides more stable solutions than LMS.
    Relation: Statistics and Computing9(4),251-263
    Data Type: article
    Appears in Collections:[Department of Statistics] Periodical Articles

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