Testing Composite Hypothesis Based on the Density Power Divergence

Article Type

Research Article

Publication Title

Sankhya B

Abstract

In any parametric inference problem, the robustness of the procedure is a real concern. A procedure which retains a high degree of efficiency under the model and simultaneously provides stable inference under data contamination is preferable in any practical situation over another procedure which achieves its efficiency at the cost of robustness or vice versa. The density power divergence family of Basu et al. (Biometrika85, 549–559 1998) provides a flexible class of divergences where the adjustment between efficiency and robustness is controlled by a single parameter β. In this paper we consider general tests of parametric hypotheses based on the density power divergence. We establish the asymptotic null distribution of the test statistic and explore its asymptotic power function. Numerical results illustrate the performance of the theory developed.

First Page

222

Last Page

262

DOI

10.1007/s13571-017-0143-0

Publication Date

11-1-2018

Comments

All Open Access, Green

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