Statistical Research Report
Preprint 6, 2000
Author(s):
M.C. Jones, N.L. Hjort, I.R. Harris, A. Basu
Title:
A comparison of related density-based minimum divergence
estimators.
Abstract:
This paper compares the minimum divergence estimator
of Basu, Harris, Hjort and Jones (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,
contain maximum likelihood as a special case, and
can be extended to the context of regression situations.
Theoretical calculations are given to compare efficiencies
under model conditions, and robustness properties are
studied and compared. Overall the two methods
are found to perform quite similarly. Some relatively small
advantages of the former method over the latter are identified.
Key words:
asymptotic relative efficiency,
divergences,
influence functions,
M-estimation,
maximum likelihood
A postscript version of the entire preprint.