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On some robust estimation procedures for quantiles based on data

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  • Yoeng-Kuan Chang
  • Deng-Yuan Huang

Abstract

This paper introduces some robust estimation procedures to estimate quantiles of a continuous random variable based on data, without any other assumptions of probability distribution. We construct a reasonable linear regression model to connect the relationship between a suitable symmetric data transformation and the approximate standard normal statistics. Statistical properties of this linear regression model and its applications are studied, including estimators of quantiles, quartile mean, quartile deviation, correlation coefficient of quantiles and standard errors of these estimators. We give some empirical examples to illustrate the statistical properties and apply our estimators to grouping data.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:32:y:2005:i:9:p:909-927
    DOI: 10.1080/02664760500163532
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    References listed on IDEAS

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    1. 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.
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