Article ID Journal Published Year Pages File Type
1149106 Journal of Statistical Planning and Inference 2010 19 Pages PDF
Abstract

We study a modification of the notion of asymptotic intermediate efficiency of statistical tests by defining it in terms of shifting alternatives. We prove a theorem providing conditions for its existence and show that this modification is closely related to the original Kallenberg's asymptotic intermediate efficiency in a quite general setting. Next, we find estimates for differences between powers of the Neyman–Pearson test under original alternatives and that of a given test under shifted alternatives. We also present some simulation results. They attest to consistency of theoretical results with observed empirical powers for quite small sample sizes.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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