Journal of Multivariate Analysis最新文献_第7页

An exponential inequality for Hilbert-valued U-statistics of i.i.d. data i.i.d数据的hilbert值u统计量的指数不等式

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2025-01-06 DOI: 10.1016/j.jmva.2025.105406

Davide Giraudo

引用次数: 0

Fisher’s legacy of directional statistics, and beyond to statistics on manifolds 费雪的方向统计的遗产，以及对流形的统计

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2025-01-03 DOI: 10.1016/j.jmva.2024.105404

Kanti V. Mardia

{"title":"Fisher’s legacy of directional statistics, and beyond to statistics on manifolds","authors":"Kanti V. Mardia","doi":"10.1016/j.jmva.2024.105404","DOIUrl":"10.1016/j.jmva.2024.105404","url":null,"abstract":"<div><div>It is not an exaggeration to say that R.A. Fisher is the Albert Einstein of Statistics. He pioneered almost all the main branches of statistics, but it is not as well known that he opened the area of Directional Statistics with his 1953 paper introducing a distribution on the sphere which is now known as the Fisher distribution. He stressed that for spherical data one should take into account that the data is on a manifold. We will describe this Fisher distribution and reanalyze his geological data. We also comment on the two goals he set himself in that paper, and on how he reinvented the von Mises distribution on the circle. Since then, many extensions of this distribution have appeared bearing Fisher’s name such as the von Mises–Fisher distribution and the matrix Fisher distribution. In fact, the subject of Directional Statistics has grown tremendously in the last two decades with new applications emerging in life sciences, image analysis, machine learning and so on. We give a recent new method of constructing the Fisher type distributions on manifolds which has been motivated by some problems in machine learning. The number of directional distributions has increased since then, including the bivariate von Mises distribution and we describe its connection to work resulting in the 2024 Nobel-winning AlphaFold (in Chemistry). Further, the subject has evolved as Statistics on Manifolds which also includes the new field of Shape Analysis, and finally, we end with a historical note pointing out some correspondence between D’Arcy Thompson and R.A. Fisher related to Shape Analysis.</div></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"207 ","pages":"Article 105404"},"PeriodicalIF":1.4,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143134409","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

SFQRA: Scaled factor-augmented quantile regression with aggregation in conditional mean forecasting SFQRA：条件均值预测中带聚集的比例因子增强分位数回归

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2025-01-03 DOI: 10.1016/j.jmva.2024.105405

Lei Shu , Yifan Hao , Yu Chen , Qing Yang

{"title":"SFQRA: Scaled factor-augmented quantile regression with aggregation in conditional mean forecasting","authors":"Lei Shu , Yifan Hao , Yu Chen , Qing Yang","doi":"10.1016/j.jmva.2024.105405","DOIUrl":"10.1016/j.jmva.2024.105405","url":null,"abstract":"<div><div>Achieving robust forecasts for a single time series with many covariates and possible nonlinear effects is a problem worth investigating. In this paper, a scaled factor-augmented quantile regression with aggregation (SFQRA) method is proposed for an effective prediction. It first estimates different conditional quantiles by introducing scaled covariates to the factor-augmented quantile regression, which not only combats the curse of dimensionality but also includes the target information in the estimation. Then the different conditional quantiles are aggregated appropriately to a robust forecast. Moreover, combining SFQRA with feature screening via an aggregated quantile correlation allows it to be extended to handle cases when only a portion of covariates is informative. The effectiveness of the proposed methods is justified theoretically, under the framework of large cross-sections and large time dimensions while no restriction is imposed on the relation between them. Various simulation studies and real data analyses demonstrate the superiority of the newly proposed method in forecasting.</div></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"207 ","pages":"Article 105405"},"PeriodicalIF":1.4,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143134412","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

Semi-functional varying coefficient mode-based regression 基于半泛函变系数模型的回归

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2025-01-01 DOI: 10.1016/j.jmva.2024.105402

Tao Wang

{"title":"Semi-functional varying coefficient mode-based regression","authors":"Tao Wang","doi":"10.1016/j.jmva.2024.105402","DOIUrl":"10.1016/j.jmva.2024.105402","url":null,"abstract":"<div><div>We propose estimating semi-functional varying coefficient regression based on the mode value through a kernel objective function, where the bandwidth included is treated as a tuning parameter to achieve efficiency and robustness. For estimation, functional principal component basis functions are utilized to approximate the slope function and functional predictor variable, while B-spline functions are employed to approximate the varying coefficient component. Under mild regularity conditions, the convergence rates of the resulting estimators for the unknown slope function and varying coefficient are established under various cases. To numerically estimate the proposed model, we recommend employing a computationally efficient mode expectation–maximization algorithm with the aid of a Gaussian kernel. The tuning parameters are selected using the mode-based Bayesian information criterion and cross-validation procedures. Built upon the generalized likelihood technique, we further develop a goodness-of-fit test to assess the constancy of varying coefficient functions and put forward a wild bootstrap procedure for estimating the corresponding critical values. The finite sample performance of the developed estimators is illustrated through Monte Carlo simulations and real data analysis related to the Tecator data. The results produced by the propounded method are compared favorably with those obtained from alternative estimation techniques.</div></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"207 ","pages":"Article 105402"},"PeriodicalIF":1.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143134414","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

Sequential estimation of high-dimensional signal plus noise models under general elliptical frameworks 一般椭圆框架下高维信号加噪声模型的序贯估计

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2024-12-30 DOI: 10.1016/j.jmva.2024.105403

Li Yanpeng , Xie Jiahui , Zhou Guoliang , Zhou Wang

引用次数: 0

On the consistency of the jackknife estimator of the asymptotic variance of spatial median 空间中值渐近方差的刀切估计的相合性

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2024-12-15 DOI: 10.1016/j.jmva.2024.105399

František Rublík

引用次数: 0

High-dimensional projection-based ANOVA test 基于高维投影的方差分析检验

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2024-12-15 DOI: 10.1016/j.jmva.2024.105401

Weihao Yu , Qi Zhang , Weiyu Li

引用次数: 0

Quadratic inference with dense functional responses 具有密集泛函响应的二次推理

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2024-12-14 DOI: 10.1016/j.jmva.2024.105400

Pratim Guha Niyogi , Ping-Shou Zhong

{"title":"Quadratic inference with dense functional responses","authors":"Pratim Guha Niyogi , Ping-Shou Zhong","doi":"10.1016/j.jmva.2024.105400","DOIUrl":"10.1016/j.jmva.2024.105400","url":null,"abstract":"<div><div>We address the challenge of estimation in the context of constant linear effect models with dense functional responses. In this framework, the conditional expectation of the response curve is represented by a linear combination of functional covariates with constant regression parameters. In this paper, we present an alternative solution by employing the quadratic inference approach, a well-established method for analyzing correlated data, to estimate the regression coefficients. Our approach leverages non-parametrically estimated basis functions, eliminating the need for choosing working correlation structures. Furthermore, we demonstrate that our method achieves a parametric <span><math><msqrt><mrow><mi>n</mi></mrow></msqrt></math></span>-convergence rate, contingent on an appropriate choice of bandwidth. This convergence is observed when the number of repeated measurements per trajectory exceeds a certain threshold, specifically, when it surpasses <span><math><msup><mrow><mi>n</mi></mrow><mrow><msub><mrow><mi>a</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow></msup></math></span>, with <span><math><mi>n</mi></math></span> representing the number of trajectories. Additionally, we establish the asymptotic normality of the resulting estimator. The performance of the proposed method is compared with that of existing methods through extensive simulation studies, where our proposed method outperforms. Real data analysis is also conducted to demonstrate the proposed method.</div></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"207 ","pages":"Article 105400"},"PeriodicalIF":1.4,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143134411","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

Asymptotics for non-degenerate multivariate U-statistics with estimated nuisance parameters under the null and local alternative hypotheses 非退化多元u统计量在零假设和局部备择假设下的渐近性

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2024-12-06 DOI: 10.1016/j.jmva.2024.105398

Alain Desgagné , Christian Genest , Frédéric Ouimet

引用次数: 0

Efficient estimation of a partially linear panel data model with cross-sectional dependence 具有截面相关性的部分线性面板数据模型的有效估计

IF 1.4 3区数学

Journal of Multivariate Analysis Pub Date : 2024-12-05 DOI: 10.1016/j.jmva.2024.105393

Alexandra Soberon , Massimiliano Mazzanti , Antonio Musolesi , Juan M. Rodriguez-Poo

引用次数: 0