首页> 外文期刊>Information Sciences: An International Journal >GENERALIZED DIVERGENCE MEASURES - INFORMATION MATRICES, AMOUNT OF INFORMATION, ASYMPTOTIC DISTRIBUTION, AND ITS APPLICATIONS TO TEST STATISTICAL HYPOTHESES
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GENERALIZED DIVERGENCE MEASURES - INFORMATION MATRICES, AMOUNT OF INFORMATION, ASYMPTOTIC DISTRIBUTION, AND ITS APPLICATIONS TO TEST STATISTICAL HYPOTHESES

机译:广义发散度量-信息矩阵,信息量,渐近分布及其在检验统计假设中的应用

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摘要

In this paper, a transformation of Csiszar's measures which generalizes the unified (r, s) measures defined by Sharma and Mittal and Taneja is presented. For these transformations, information matrices associated to a differential metric in the direction to the tangent space are obtained, as well as the amount of information resulting from parameter perturbation in the direction of coordinate axes. Finally, the asymptotic distribution of information matrices and the amount of information and its applications to test statistical hypotheses are obtained. [References: 28]
机译:在本文中,提出了Csiszar测度的一种转换,它概括了Sharma和Mittal和Taneja定义的统一(r,s)测度。对于这些变换,获得与在切线空间方向上的微分度量相关的信息矩阵,以及在坐标轴方向上由参数摄动产生的信息量。最后,获得了信息矩阵的渐近分布和信息量及其在检验统计假设中的应用。 [参考:28]

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