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Bayesian group regularization in generalized linear models with a continuous spike-and-slab prior 具有连续峰板先验的广义线性模型的贝叶斯群正则化
IF 1.4 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-10-18 DOI: 10.1007/s10463-025-00964-7
Ray Bai
{"title":"Bayesian group regularization in generalized linear models with a continuous spike-and-slab prior","authors":"Ray Bai","doi":"10.1007/s10463-025-00964-7","DOIUrl":"10.1007/s10463-025-00964-7","url":null,"abstract":"<div><p>We study Bayesian group-regularized estimation in high-dimensional generalized linear models (GLMs) under a continuous spike-and-slab prior. Our framework covers both canonical and non-canonical link functions and subsumes logistic, Poisson, negative binomial, and Gaussian regression with group sparsity. We obtain the minimax <span>(ell _2)</span> convergence rate for both a maximum a posteriori (MAP) estimator and the full posterior distribution under our prior. Our theoretical results thus justify the use of the posterior mode as a point estimator. The posterior distribution also contracts at the same rate as the MAP estimator, an attractive feature of our approach which is not the case for the group lasso. For computation, we propose expectation-maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms. We illustrate our method through simulations and a real data application on predicting human immunodeficiency virus (HIV) drug resistance from protein sequences.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 5","pages":"839 - 872"},"PeriodicalIF":1.4,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Empirical likelihood simultaneous confidence band for conditional variance function 条件方差函数的经验似然同时置信带
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-09-30 DOI: 10.1007/s10463-025-00953-w
Manandhar Sareeta, Li Cai, Rong Liu, Yichuan Zhao
{"title":"Empirical likelihood simultaneous confidence band for conditional variance function","authors":"Manandhar Sareeta,&nbsp;Li Cai,&nbsp;Rong Liu,&nbsp;Yichuan Zhao","doi":"10.1007/s10463-025-00953-w","DOIUrl":"10.1007/s10463-025-00953-w","url":null,"abstract":"<div><p>Simultaneous confidence bands (SCBs) are powerful global inference tools for establishing a band around the true conditional variance function with a specified confidence level for all covariate values. In this paper, we propose empirical likelihood-based SCBs to address this issue. The proposed empirical likelihood-based bands provide advantages such as enhanced coverage accuracy, straightforward implementation, and automatic avoidance of estimating variances and studentizing. The results of the simulation and empirical examples demonstrate that these methods are effective in estimating the volatility of a process and can be used to generate forecasts of future volatility.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 3","pages":"459 - 477"},"PeriodicalIF":0.6,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10463-025-00953-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Simultaneously sparse and low-rank matrix estimation via (l_1)-norm and nonconvex regularization 同时通过(l_1) -范数和非凸正则化进行稀疏和低秩矩阵估计
IF 1.4 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-09-12 DOI: 10.1007/s10463-025-00954-9
Ling Peng, Shanshan Tang, Fei Huang, Weiying Ping
{"title":"Simultaneously sparse and low-rank matrix estimation via (l_1)-norm and nonconvex regularization","authors":"Ling Peng,&nbsp;Shanshan Tang,&nbsp;Fei Huang,&nbsp;Weiying Ping","doi":"10.1007/s10463-025-00954-9","DOIUrl":"10.1007/s10463-025-00954-9","url":null,"abstract":"<div><p>This paper addresses the challenge of low-rank matrix estimation in high-dimensional settings, where the dimensions of the matrix far exceed the sample size. To overcome this, we propose a novel approach that integrates sparsity and nonconvex regularization. Our method employs nonconvex penalties, such as the smoothly clipped absolute deviation (SCAD) and the minimax concave penalty (MCP), to reduce estimation bias and improve convergence rates. We develop efficient optimization algorithms to handle the resulting complex problems. Through rigorous theoretical analysis and extensive empirical evaluations, we demonstrate the robustness and effectiveness of our approach in various high-dimensional contexts.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 4","pages":"603 - 625"},"PeriodicalIF":1.4,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148357738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Debiased group lasso for multiple compositional data 多组分数据去偏组套索
IF 1.4 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-09-03 DOI: 10.1007/s10463-025-00956-7
Sujin Lee, Sungkyu Jung
{"title":"Debiased group lasso for multiple compositional data","authors":"Sujin Lee,&nbsp;Sungkyu Jung","doi":"10.1007/s10463-025-00956-7","DOIUrl":"10.1007/s10463-025-00956-7","url":null,"abstract":"<div><p>This paper addresses the challenge of variable selection and statistical inference in multiple compositional data, particularly in the context of multi-site human microbiome studies. We propose a novel extension of the group lasso framework to handle compositional covariates through the multiple compositional regression model. Our approach, which incorporates both compositional constraints and a debiasing procedure, enables asymptotically unbiased and normally distributed estimates for grouped coefficients. We develop statistical significance tests based on asymptotic chi-squared statistics for grouped variables and provide rigorous theoretical guarantees on estimation error bounds. Through extensive simulation studies, we demonstrate that the proposed method outperforms traditional approaches, especially in scenarios with weak signals, by achieving higher positive predictive values. Finally, we apply the method to a human microbiome dataset to identify bacterial taxa associated with cholesterol levels, showcasing the practical utility of our approach.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 4","pages":"627 - 651"},"PeriodicalIF":1.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148357742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Statistical inference for the dynamic time warping distance, with application to abnormal time-series detection 动态时间翘曲距离的统计推断，并应用于异常时间序列检测
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-09-03 DOI: 10.1007/s10463-025-00955-8
Vo Nguyen Le Duy, Ichiro Takeuchi
{"title":"Statistical inference for the dynamic time warping distance, with application to abnormal time-series detection","authors":"Vo Nguyen Le Duy,&nbsp;Ichiro Takeuchi","doi":"10.1007/s10463-025-00955-8","DOIUrl":"10.1007/s10463-025-00955-8","url":null,"abstract":"<div><p>We propose a novel method for conducting statistical inference on the similarity between two time-series by considering a hypothesis test on the Dynamic Time Warping (DTW) distance. The key strength of the proposed method lies in its ability to control the probability of false detection rate in high-stakes decision-making scenarios when the DTW distance is used. Compared to the literature, we presents a unique challenge in conducing a statistical inference on the DTW distance for controlling the false detection rate. We overcome the challenge by leveraging the concept of Selective Inference. Specifically, we carefully examine the computation process of the DTW distance whose operations can be characterized by quadratic inequalities, and prove that a satisfactory inference on the DTW distance is indeed possible. Experiments conducted on both synthetic and real-world datasets robustly support our theoretical results, showcasing the superior performance of the proposed method.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 3","pages":"515 - 543"},"PeriodicalIF":0.6,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Restricted estimation in partially linear varying coefficient errors-in-variables models with missing response variables 缺失响应变量的部分线性变系数变量误差模型的约束估计
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-08-30 DOI: 10.1007/s10463-025-00948-7
Xiaoqian Zheng, Xuejun Wang, Liangxue Li
{"title":"Restricted estimation in partially linear varying coefficient errors-in-variables models with missing response variables","authors":"Xiaoqian Zheng,&nbsp;Xuejun Wang,&nbsp;Liangxue Li","doi":"10.1007/s10463-025-00948-7","DOIUrl":"10.1007/s10463-025-00948-7","url":null,"abstract":"<div><p>In numerous application areas of regression analysis, prior information about the relationship between explanatory variables and response variables is usually available, and can be expressed as precise restrictions on regression coefficients. In this paper, under exact linear restrictions, we consider the partially linear varying coefficient model with missing response variables and measurement errors potentially in all the covariates. By combining local bias-corrected profile least squares method and Lagrange multiplier method, two types of restricted estimators of the parametric vectors and nonparametric functions are introduced based on complete-case data and an imputation technique, respectively, and their asymptotic distributions are also derived under some mild conditions. Simulation experiments are carried out to evaluate the finite sample performance of the proposed methodologies. Furthermore, a real example in epidemiology is provided for illustration.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 3","pages":"351 - 397"},"PeriodicalIF":0.6,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Asymptotic normality of multivariate frequency polygons for stationary random fields 平稳随机场多变量频率多边形的渐近正态性
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-08-19 DOI: 10.1007/s10463-025-00952-x
Michel Carbon, Thierry Duchesne
{"title":"Asymptotic normality of multivariate frequency polygons for stationary random fields","authors":"Michel Carbon,&nbsp;Thierry Duchesne","doi":"10.1007/s10463-025-00952-x","DOIUrl":"10.1007/s10463-025-00952-x","url":null,"abstract":"<div><p>The purpose of this paper is to investigate the asymptotic normality of the multivariate frequency polygon as a density estimator of a stationary mixing random field indexed by multidimensional lattice points space <span>(mathbb {Z}^N)</span>. Results on weak convergence of the estimator are established, including a simple analytic form for its asymptotic variance. A consistent estimator is proposed for this variance. Simulations confirm the theoretical results. Bias correction and appropriate choices of the bandwidths are discussed. The results apply to many spatial random models, such as spatial autoregressive models, spatio-temporal geostatistical models, spatial epidemiology.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 2","pages":"297 - 326"},"PeriodicalIF":0.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147352665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Optimal averaging estimator of heterogeneous treatment effects for single-index models 单指标模型异质性处理效果的最优平均估计
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-08-19 DOI: 10.1007/s10463-025-00951-y
Na Li, Maoyuan Wang, Yu Fei, Xinyu Zhang
{"title":"Optimal averaging estimator of heterogeneous treatment effects for single-index models","authors":"Na Li,&nbsp;Maoyuan Wang,&nbsp;Yu Fei,&nbsp;Xinyu Zhang","doi":"10.1007/s10463-025-00951-y","DOIUrl":"10.1007/s10463-025-00951-y","url":null,"abstract":"<div><p>In the estimation of heterogeneous treatment effects, model uncertainty often exists for reasons such as doubt about which variable or model should be used. To handle the model uncertainty, we offer a model averaging method by assembling the estimators obtained from multiple single-index models. We use <i>J</i>-fold cross-validation to choose averaging weights and investigate the asymptotic properties of the proposed method under two settings: (1) all candidate models are misspecified; and (2) candidate models include correct models. In the first setting, we show that our method has asymptotic optimality in the sense of achieving the lowest possible squared loss, and the selected weights can converge to the optimal weights. In the second setting, our proposed weighting scheme asymptotically assigns all weights to the correct models, which leads to a consistency of model averaging estimator. Two simulation studies and an empirical application are used to illustrate the merits of our method.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 3","pages":"435 - 458"},"PeriodicalIF":0.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Discussion of “Mode-based estimation of the center of symmetry” 关于“基于模态的对称中心估计”的讨论
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-31 DOI: 10.1007/s10463-025-00944-x
Juan Carlos Pardo-Fernández
{"title":"Discussion of “Mode-based estimation of the center of symmetry”","authors":"Juan Carlos Pardo-Fernández","doi":"10.1007/s10463-025-00944-x","DOIUrl":"10.1007/s10463-025-00944-x","url":null,"abstract":"","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"77 5","pages":"723 - 725"},"PeriodicalIF":0.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Rejoinder to the discussion of “Mode-based estimation of the center of symmetry” 对“基于模态的对称中心估计”讨论的回答
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-31 DOI: 10.1007/s10463-025-00945-w
José E. Chacón, Javier Fernández Serrano
{"title":"Rejoinder to the discussion of “Mode-based estimation of the center of symmetry”","authors":"José E. Chacón,&nbsp;Javier Fernández Serrano","doi":"10.1007/s10463-025-00945-w","DOIUrl":"10.1007/s10463-025-00945-w","url":null,"abstract":"","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"77 5","pages":"727 - 730"},"PeriodicalIF":0.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
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