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Adaptive M-estimation using Selector Statistics in Location Model
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 Title & Authors
Adaptive M-estimation using Selector Statistics in Location Model
Han, Sang-Moon;
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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.
 Keywords
robust;selector statistics;M-estimators;
 Language
Korean
 Cited by
1.
Adaptive M-estimation in Regression Model,;

Communications for Statistical Applications and Methods, 2003. vol.10. 3, pp.859-871 crossref(new window)
1.
Adaptive M-estimation in Regression Model, Communications for Statistical Applications and Methods, 2003, 10, 3, 859  crossref(new windwow)
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