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On some data oriented robust estimation procedures for means

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  • Ren-Fen Lee
  • Deng-Yuan Huang

Abstract

Data oriented to estimate means is very important for large data sets. Since outliers usually occur, the trimmed mean is a robust estimator of locations. After building a reasonable linear model to explain the relationship between the suitably transformed symmetric data and the approximately standardized normal statistics, we find the trimmed proportion based on the smallest variance of trimmed means. The related statistical inference is also discussed. An empirical study based on an annual survey about inbound visitors in the Taiwan area is used to achieve our goal in deciding the trimmed proportion. In this study, we propose a complete procedure to attain the goal.

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  • Ren-Fen Lee & Deng-Yuan Huang, 2003. "On some data oriented robust estimation procedures for means," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(6), pages 625-634.
    • Handle: RePEc:taf:japsta:v:30:y:2003:i:6:p:625-634
    DOI: 10.1080/0266476032000053727
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    Cited by:

    1. Sibel Balci & Aysen Dener Akkaya, 2015. "Robust pairwise multiple comparisons under short-tailed symmetric distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2293-2306, November.
    2. Yoeng-Kuan Chang & Deng-Yuan Huang, 2005. "On some robust estimation procedures for quantiles based on data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(9), pages 909-927.

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