摘要翻译:
乘积概率性质,在文献中被称为统计独立性,首先被检验。然后引入了广义熵,它们都给出了香农熵的推广。结果表明,递归性公设的性质自动决定了Shannon熵的对数函数形式。由于香农熵的对数性质,当应用于具有乘积概率性质的情形时,自然产生可加性。人们认为,自然过程是不可加性的,例如,在统计力学中,甚至在乘积概率性质的情况下,这种不可加性也是很重要的。由于涉及到一个导致对数函数的递归性公设,可加性也可以成立。介绍了一些推广,包括Mathai的广义熵,并研究了一些性质。研究了Mathai熵导致路径模型、指数和幂律行为以及相关微分方程的情况。本文还探讨了马泰熵与克里奇“不精确性”测度的关系。
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英文标题:
《On generalized entropy measures and pathways》
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作者:
A.M. Mathai, H.J. Haubold
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最新提交年份:
2007
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分类信息:
一级分类:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类:Physics 物理学
二级分类:Statistical Mechanics 统计力学
分类描述:Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变,热力学,场论,非平衡现象,重整化群和标度,可积模型,湍流
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一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
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英文摘要:
Product probability property, known in the literature as statistical independence, is examined first. Then generalized entropies are introduced, all of which give generalizations to Shannon entropy. It is shown that the nature of the recursivity postulate automatically determines the logarithmic functional form for Shannon entropy. Due to the logarithmic nature, Shannon entropy naturally gives rise to additivity, when applied to situations having product probability property. It is argued that the natural process is non-additivity, important, for example, in statistical mechanics, even in product probability property situations and additivity can hold due to the involvement of a recursivity postulate leading to a logarithmic function. Generalizations, including Mathai's generalized entropy are introduced and some of the properties are examined. Situations are examined where Mathai's entropy leads to pathway models, exponential and power law behavior and related differential equations. Connection of Mathai's entropy to Kerridge's measure of "inaccuracy" is also explored.
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PDF链接:
https://arxiv.org/pdf/704.0326


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