关于Cressie-Read散度统计族成员的p值

IF 0.6 Q4 STATISTICS & PROBABILITY Austrian Journal of Statistics Pub Date : 2023-09-11 DOI:10.17713/ajs.v52i5.1607
Eric Beh, Wang Ting-Wu
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引用次数: 0

摘要

几年前,《华尔街日报》上发表了一篇论文,提出了皮尔逊卡方统计量p值的封闭近似。进行了广泛的经验和模拟研究,结果表明,与我们认为的“真实”p值(使用基R函数获得)相比,近似提供了非常准确的p值。然而,重要的是要注意,皮尔逊的卡方统计量是克雷西-里德散度统计量家族的一个特殊情况,例如,对数似然比统计量,弗里曼-杜克统计量和克雷西-里德统计量。因此,本文通过证明p值的封闭形式近似适用于Cressie-Read散度统计族的任何成员,采用了先前发表的p值的封闭形式近似。我们还给出了两个进一步的封闭形式近似值,并通过分析三个不同样本量、自由度和关联的统计显著性的列联表来评估它们的准确性。
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On the P-value for Members of the Cressie-Read Family of Divergence Statistics
A few years ago a paper appeared in this Journal that proposed a closed-form approximation of the p-value for Pearson's chi-squared statistic. Extensive empirical and simulation studies were performed and it was shown that the approximation provides very accurate p-values when compared with what we considered to be the ``true'' p-value (obtained using a base R function). It is important to note, however, that Pearson's chi-squared statistic is a special case of the Cressie-Read family of divergence statistics as is, for example, the log-likelihood ratio statistic, the Freeman-Tukey statistic and the Cressie-Read statistic. Therefore, this paper adapts the previously published closed form approximation of the p-value by demonstrating its applicability to any member of the Cressie-Read family of divergence statistics. We also give two further closed form approximations and assess their accuracy by analysing three contingency tables of varying sample size, degrees of freedom and statistical significance of the association.
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来源期刊
Austrian Journal of Statistics
Austrian Journal of Statistics STATISTICS & PROBABILITY-
CiteScore
1.10
自引率
0.00%
发文量
30
审稿时长
24 weeks
期刊介绍: The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.
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