Journal of Multivariate Analysis最新文献_第9页

Lp-norm spherical copulas lp范数球面联

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-29 DOI: 10.1016/j.jmva.2023.105262

Carole Bernard , Alfred Müller , Marco Oesting

引用次数: 0

Copula modeling from Abe Sklar to the present day 从Abe Sklar到现在的Copula模型

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-29 DOI: 10.1016/j.jmva.2023.105278

Christian Genest , Ostap Okhrin , Taras Bodnar

引用次数: 0

fastMI: A fast and consistent copula-based nonparametric estimator of mutual information fastMI:一种快速且一致的互信息非参数估计器

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-29 DOI: 10.1016/j.jmva.2023.105270

Soumik Purkayastha , Peter X.-K. Song

{"title":"fastMI: A fast and consistent copula-based nonparametric estimator of mutual information","authors":"Soumik Purkayastha , Peter X.-K. Song","doi":"10.1016/j.jmva.2023.105270","DOIUrl":"10.1016/j.jmva.2023.105270","url":null,"abstract":"<div>As a fundamental concept in information theory, mutual information (<math><mrow><mi>M</mi><mi>I</mi></mrow></math>) has been commonly applied to quantify association between random vectors. Most existing nonparametric estimators of <math><mrow><mi>M</mi><mi>I</mi></mrow></math> have unstable statistical performance since they involve parameter tuning. We develop a consistent and powerful estimator, called fastMI, that does not incur any parameter tuning. Based on a copula formulation, fastMI estimates <math><mrow><mi>M</mi><mi>I</mi></mrow></math> by leveraging Fast Fourier transform-based estimation of the underlying density. Extensive simulation studies reveal that fastMI outperforms state-of-the-art estimators with improved estimation accuracy and reduced run time for large data sets. fastMI provides a powerful test for independence that exhibits satisfactory type I error control. Anticipating that it will be a powerful tool in estimating mutual information in a broad range of data, we develop an R package fastMI for broader dissemination.</div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"201 ","pages":"Article 105270"},"PeriodicalIF":1.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138516874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Penalized estimation of hierarchical Archimedean copula 等级阿基米德联结的惩罚估计

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-29 DOI: 10.1016/j.jmva.2023.105274

Ostap Okhrin , Alexander Ristig

引用次数: 0

A multivariate skew-normal-Tukey-h distribution 多元偏态-正态- tukey -h分布

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-28 DOI: 10.1016/j.jmva.2023.105260

Sagnik Mondal, Marc G. Genton

{"title":"A multivariate skew-normal-Tukey-h distribution","authors":"Sagnik Mondal, Marc G. Genton","doi":"10.1016/j.jmva.2023.105260","DOIUrl":"https://doi.org/10.1016/j.jmva.2023.105260","url":null,"abstract":"<div>We introduce a new family of multivariate distributions by taking the component-wise Tukey-<math><mi>h</mi></math> transformation of a random vector following a skew-normal distribution with an alternative parameterization. The proposed distribution is named the skew-normal-Tukey-<math><mi>h</mi></math> distribution and is an extension of the skew-normal distribution for handling heavy-tailed data. We compare this proposed distribution to the skew-<math><mi>t</mi></math> distribution, which is another extension of the skew-normal distribution for modeling tail-thickness, and demonstrate that when there are substantial differences in marginal kurtosis, the proposed distribution is more appropriate. Moreover, we derive many appealing stochastic properties of the proposed distribution and provide a methodology for the estimation of the parameters that can be applied to large dimensions. Using simulations, as well as a wine and a wind speed data application, we illustrate how to draw inferences based on the multivariate skew-normal-Tukey-<math><mi>h</mi></math> distribution.</div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"200 ","pages":"Article 105260"},"PeriodicalIF":1.6,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138484142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Testing homogeneity in high dimensional data through random projections 通过随机投影检验高维数据的同质性

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-27 DOI: 10.1016/j.jmva.2023.105252

Tao Qiu , Qintong Zhang , Yuanyuan Fang , Wangli Xu

{"title":"Testing homogeneity in high dimensional data through random projections","authors":"Tao Qiu , Qintong Zhang , Yuanyuan Fang , Wangli Xu","doi":"10.1016/j.jmva.2023.105252","DOIUrl":"https://doi.org/10.1016/j.jmva.2023.105252","url":null,"abstract":"<div>Testing for homogeneity of two random vectors is a fundamental problem in statistics. In the past two decades, numerous efforts have been made to detect heterogeneity when the random vectors are multivariate or even high dimensional. Due to the “curse of dimensionality”, existing tests based on Euclidean distance may fail to capture the overall homogeneity in high-dimensional settings while can only capture the moment discrepancy. To address this issue, we propose a fully nonparametric test for homogeneity of two random vectors. Our method involves randomly selecting two subspaces consisting of components of the vectors, projecting the subspaces onto one-dimensional spaces, respectively, and constructing the test statistic using the Cramér–von Mises distance of the projections. To enhance the performance, we repeatedly implement this procedure to construct the final test statistic. Theoretically, if the replication time tends to infinity, we can avoid potential power loss caused by lousy directions. Owing to the <math><mi>U</mi></math>-statistic theory, the asymptotic null distribution of our proposed test is standard normal, regardless of the parent distributions of the random samples and the relationship between data dimensions and sample sizes. As a result, no re-sampling procedure is needed to determine critical values. The empirical size and power of the proposed test are demonstrated through numerical simulations.</div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"200 ","pages":"Article 105252"},"PeriodicalIF":1.6,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138453609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-dimensional factor copula models with estimation of latent variables 具有潜在变量估计的高维因子联结模型

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-25 DOI: 10.1016/j.jmva.2023.105263

Xinyao Fan, Harry Joe

引用次数: 0

A class of smooth, possibly data-adaptive nonparametric copula estimators containing the empirical beta copula 一类光滑的、可能自适应的非参数共轭估计量，其中包含经验共轭

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-24 DOI: 10.1016/j.jmva.2023.105269

Ivan Kojadinovic , Bingqing Yi

引用次数: 0

Comparison of correlation-based measures of concordance in terms of asymptotic variance 从渐近方差的角度比较基于相关的一致性度量

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-24 DOI: 10.1016/j.jmva.2023.105265

Takaaki Koike , Marius Hofert

{"title":"Comparison of correlation-based measures of concordance in terms of asymptotic variance","authors":"Takaaki Koike , Marius Hofert","doi":"10.1016/j.jmva.2023.105265","DOIUrl":"10.1016/j.jmva.2023.105265","url":null,"abstract":"<div>We compare measures of concordance that arise as Pearson’s linear correlation coefficient between two random variables transformed so that they follow the so-called concordance-inducing distributions. The class of such transformed rank correlations includes Spearman’s rho, Blomqvist’s beta and van der Waerden’s coefficient. When only the standard axioms of measures of concordance are required, it is not always clear which transformed rank correlation is most suitable to use. To address this question, we compare measures of concordance in terms of their best and worst asymptotic variances of some canonical estimators over a certain set of dependence structures. A simple criterion derived from this approach is that concordance-inducing distributions with smaller fourth moment are more preferable. In particular, we show that Blomqvist’s beta is the optimal transformed rank correlation in this sense, and Spearman’s rho outperforms van der Waerden’s coefficient. Moreover, we find that Kendall’s tau, although it is not a transformed rank correlation of that nature, shares a certain optimal structure with Blomqvist’s beta.</div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"201 ","pages":"Article 105265"},"PeriodicalIF":1.6,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138503931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multivariate tail dependence and local stochastic dominance 多元尾依赖与局部随机优势

IF 1.6 3区数学

Journal of Multivariate Analysis Pub Date : 2023-11-24 DOI: 10.1016/j.jmva.2023.105267

Karl Friedrich Siburg, Christopher Strothmann

引用次数: 0