广义Giniγ的矩阵相容性和相关混合表示

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2022-12-12 DOI:10.1002/cjs.11748
Takaaki Koike, Marius Hofert
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引用次数: 3

摘要

研究了用皮尔逊相关系数表示的一致性度量。我们首先对变换进行表征,使得变换后的随机变量之间的相关系数是一致性的度量。这种表征改进了Hofert和Koike(2019)的表征,并涵盖了导致例如Blomqvistβ的非连续变换。然后,我们推广了Giniγ,并证明了推广的Giniγ可以用一致性度量的混合表示,这些一致性度量被写成变换后的随机变量之间的Pearson相关系数。作为相关混合表示的一个应用,我们导出了广义Gini’s gamma相容集的下界和上界,即所有可能的平方矩阵的集合,其条目是成对的二元广义Gini‘s gamma。
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Matrix compatibility and correlation mixture representation of generalized Gini's gamma

Representations of measures of concordance in terms of Pearson's correlation coefficient are studied. All transforms of random variables are characterized such that the correlation coefficient of the transformed random variables is a measure of concordance. Gini's gamma then is generalized and it is shown that the resulting generalized Gini's gamma can be represented as a mixture of measures of concordance that are Pearson's correlation coefficients of transformed random variables. As an application of this correlation mixture representation of generalized Gini's gamma, lower and upper bounds of the compatible set of generalized Gini's gamma, i.e., the collection of all square matrices of pairwise generalized Gini's gammas, are derived.

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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
62
审稿时长
>12 weeks
期刊介绍: The Canadian Journal of Statistics is the official journal of the Statistical Society of Canada. It has a reputation internationally as an excellent journal. The editorial board is comprised of statistical scientists with applied, computational, methodological, theoretical and probabilistic interests. Their role is to ensure that the journal continues to provide an international forum for the discipline of Statistics. The journal seeks papers making broad points of interest to many readers, whereas papers making important points of more specific interest are better placed in more specialized journals. The levels of innovation and impact are key in the evaluation of submitted manuscripts.
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Issue Information Issue Information Issue Information Censored autoregressive regression models with Student-t innovations Acknowledgement of referees' services remerciements aux membres des jurys
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