Jones, M.C.; Hjort, N.L.; Harris, I.R. and Basu, A.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1093/biomet/88.3.865|
|Google Scholar:||Look up in Google Scholar|
This paper compares the minimum divergence estimator of Basu et al. (1998) to a competing minimum divergence estimator which turns out to be equivalent to a method proposed from a different perspective by Windham (1995). Both methods can be applied for any parametric model and contain maximum likelihood as a special case. Efficiencies are compared under model conditions, and robustness properties are studied. Overall the two methods are found to perform quite similarly. Some relatively small advantages of the former method over the latter are identified.
|Item Type:||Journal Article|
|Keywords:||asymptotic relative efficiency; Asymptotic relative; divergence; influence function; maximum likelihood; M-estimation; robustness;|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||M. C. Jones|
|Date Deposited:||05 Jun 2006|
|Last Modified:||02 Aug 2016 12:52|
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