Testing Composite Null Hypothesis Based on $S$-Divergences

Abstract

We present a robust test for composite null hypothesis based on the general $S$-divergence family. This requires a non-trivial extension of the results of Ghosh et al.~(2015). We derive the asymptotic and theoretical robustness properties of the resulting test along with the properties of the minimum $S$-divergence estimators under parameter restrictions imposed by the null hypothesis. An illustration in the context of the normal model is also presented.

13 pages

References in corpus (5)

• On the Robustness of a Divergence based Test of Simple Statistical Hypotheses
• Testing Composite Hypothesis based on the Density Power Divergence
• Asymptotic Properties of Minimum S-Divergence Estimator for Discrete Models
• The Minimum S-Divergence Estimator under Continuous Models: The Basu-Lindsay Approach
• Influence Function Analysis of the Restricted Minimum Divergence Estimators : A General Form

Cited by in corpus (2)

• Testing Composite Hypothesis based on the Density Power Divergence
• A New Family of Divergences Originating from Model Adequacy Tests and Application to Robust Statistical Inference