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Asymptotic Results on a General Class of Empirical Statistics: Power and Confidence Interval Properties

机译:一般经验统计类别上的渐近结果:幂和置信区间属性

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摘要

We consider a very general class of empirical statistics that includes (a) empirical discrepancy (ED) statistics, (b) generalized empirical exponential family likelihood statistics, (c) generalized empirical likelihood statistics, (d) empirical statistics arising from Bayesian considerations, and (e) Bartlett-type adjusted versions of ED statistics. With reference to this general class, we investigate higher order asymptotics on power and expected lengths of confidence intervals. For (b)-(e), such results have been hitherto unexplored. Furthermore, our findings help in understanding the presently known results on the subclass (a) from a wider perspective.
机译:我们考虑一类非常普遍的经验统计,包括(a)经验差异(ED)统计,(b)广义经验指数家庭似然统计,(c)广义经验似然统计,(d)由贝叶斯考虑产生的经验统计,以及(e)ED统计的Bartlett型调整版本。参照该一般类别,我们研究幂和预期置信区间长度的高阶渐近性。对于(b)-(e),迄今尚未探索这种结果。此外,我们的发现有助于从更广泛的角度理解关于(a)子类的当前已知结果。

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