论基于绝对矩的 L 矩上限

IF 0.9 4区 数学 Q3 STATISTICS & PROBABILITY
M.C. Jones , N. Balakrishnan
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引用次数: 0

摘要

一些基于绝对矩的基尼均值差上限被扩展到一般 L 矩。探讨了通过对绝对矩中心的替代选择来改进某些界限。对不同的界限进行了数值比较。给出了基尼均值差达到上限的分布。扩展到修剪 L 矩,进而扩展到概率加权矩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On absolute moment-based upper bounds for L-moments

A number of absolute moment-based upper bounds for Gini’s mean difference are extended to general L-moments. Improvement of some bounds by alternative choice of centre for the absolute moments is explored. Different bounds are compared numerically. The distribution for which upper bounds for Gini’s mean difference are attained is given. Extension is made to trimmed L-moments and hence to probability weighted moments.

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来源期刊
Statistics & Probability Letters
Statistics & Probability Letters 数学-统计学与概率论
CiteScore
1.60
自引率
0.00%
发文量
173
审稿时长
6 months
期刊介绍: Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature. Statistics & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission. The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability. The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published.
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