Cumulative past Fisher information measure and its extensions

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
N. Balakrishnan, O. Kharazmi
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引用次数: 0

Abstract

. In this work, we define the cumulative past Fisher (CPF) information and the relative cumulative past Fisher (RCRF) information measures for parameter as well as for the distribution function of the underlying random variables. We show that these cumulative past Fisher information measures can be expressed in terms of the reversed hazard rate function. We also define three extensions of the CPF information measure. Further, we study these cumulative information measures and their Bayes versions for some well-known models used in reliability, economics and survival analysis. The associated results reveal some interesting connections between the proposed Fisher type information measures with some well-known information divergences and reliability measures.
累积过去费雪信息测度及其扩展
在这项工作中,我们定义了参数和潜在随机变量分布函数的累积过去Fisher(CPF)信息和相对累计过去Fisher(RCRF)信息度量。我们证明了这些累积的过去Fisher信息度量可以用反向危险率函数来表示。我们还定义了CPF信息度量的三个扩展。此外,我们研究了一些用于可靠性、经济性和生存分析的著名模型的这些累积信息度量及其贝叶斯版本。相关结果揭示了所提出的Fisher型信息测度与一些众所周知的信息偏差和可靠性测度之间的一些有趣的联系。
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来源期刊
CiteScore
1.60
自引率
10.00%
发文量
30
审稿时长
>12 weeks
期刊介绍: The Brazilian Journal of Probability and Statistics aims to publish high quality research papers in applied probability, applied statistics, computational statistics, mathematical statistics, probability theory and stochastic processes. More specifically, the following types of contributions will be considered: (i) Original articles dealing with methodological developments, comparison of competing techniques or their computational aspects. (ii) Original articles developing theoretical results. (iii) Articles that contain novel applications of existing methodologies to practical problems. For these papers the focus is in the importance and originality of the applied problem, as well as, applications of the best available methodologies to solve it. (iv) Survey articles containing a thorough coverage of topics of broad interest to probability and statistics. The journal will occasionally publish book reviews, invited papers and essays on the teaching of statistics.
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