期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2015
卷号：77
期号：2
页码：380-407
DOI：10.1007/s13171-014-0063-2
语种：English
出版社：Indian Statistical Institute
摘要：Robust inference based on the minimization of statistical divergences has proved to be a useful alternative to the classical techniques based on maximum likelihood and related methods. Recently Ghosh et al. ( 2013b ) proposed a general class of divergence measures, namely the S -Divergence Family and discussed its usefulness in robust parametric estimation through some numerical illustrations. In this present paper, we develop the asymptotic properties of the proposed minimum S -Divergence estimators under discrete models.
Loading...
