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http://dx.doi.org/10.7465/jkdi.2015.26.3.549

A study on tuning parameter selection for MDPDE  

Yu, Donghyeon (Department of Statistics, Keimyung University)
Kim, Byungsoo (Department of Statistics, Yeungnam University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.3, 2015 , pp. 549-559 More about this Journal
Abstract
The MDPDE is an attractive alternative to maximum likelihood estimator because of the strong robustness properties that it inherently possess. The characteristics of MDPDE can be varied with the tuning parameter, in general, there is a trade-off between robustness and asymptotic efficiency. Hence, selection of optimal tuning parameter is important but complicated task. In this study, we introduce two optimal tuning parameter selection methods proposed by Fujisawa and Eguchi (2005) and Warwick (2006). Through simulation study, we found out that Warwick's method yields excessively small optimal tuning parameter in certain cases while Fujisawa and Eguchi's method performs well. Therefore, we think Fujisawa and Eguchi's method can be used commonly for finding optimal tuning parameter of MDPDE.
Keywords
Asymptotic efficiency; minimum distance estimator; robustness; tuning parameter;
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Times Cited By KSCI : 1  (Citation Analysis)
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