Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Adaptive M-estimation using Selector Statistics in Location Model

  • Han, Sang-Moon (Department of Computer Science and Statistics, University of Seoul)
  • Published : 2002.08.01
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Abstract

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the center of symmetric and continuous underlying distributions. This selector statistics is based on the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying distributions. In this paper, we use the functions of sample quantiles as selector statistics and determine the suitable quantile points based on maximizing the distance index to discriminate distributions under consideration. In Monte Carlo study, this robust estimation method works pretty good in wide range of underlying distributions.

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References

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Cited by

  1. Adaptive M-estimation in Regression Model vol.10, pp.3, 2003, https://doi.org/10.5351/CKSS.2003.10.3.859