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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/s10463-025-00943-y
Hideitsu Hino
{"title":"Discussion of “Mode-based estimation of the center of symmetry”","authors":"Hideitsu Hino","doi":"10.1007/s10463-025-00943-y","DOIUrl":"10.1007/s10463-025-00943-y","url":null,"abstract":"","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"77 5","pages":"719 - 721"},"PeriodicalIF":0.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923282","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
Mode-based estimation of the center of symmetry 基于模态的对称中心估计
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-31 DOI: 10.1007/s10463-025-00942-z
José E. Chacón, Javier Fernández Serrano
{"title":"Mode-based estimation of the center of symmetry","authors":"José E. Chacón,&nbsp;Javier Fernández Serrano","doi":"10.1007/s10463-025-00942-z","DOIUrl":"10.1007/s10463-025-00942-z","url":null,"abstract":"<div><p>In the mean-median-mode triad of univariate centrality measures, the mode has been overlooked for estimating the center of symmetry in continuous and unimodal settings. This paper expands on the connection between kernel mode estimators and M-estimators for location, bridging the gap between the nonparametrics and robust statistics communities. The variance of modal estimators is studied in terms of a bandwidth parameter, establishing conditions for an optimal solution that outperforms the household sample mean. A purely nonparametric approach is adopted, modeling heavy-tailedness through regular variation. The results lead to an estimator proposal that includes a novel one-parameter family of kernels with compact support, offering extra robustness and efficiency. The effectiveness and versatility of the new method are demonstrated in a real-world case study and a thorough simulation study, comparing favorably to traditional and more competitive alternatives. Several myths about the mode are clarified along the way, reopening the quest for flexible and efficient nonparametric estimators.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"77 5","pages":"685 - 717"},"PeriodicalIF":0.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923283","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
Tests for independence against regression and expectation dependence 针对回归和期望依赖的独立性测试
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-30 DOI: 10.1007/s10463-025-00949-6
Sudheesh K. Kattumannil, Deepesh Bhati, Isha Dewan
{"title":"Tests for independence against regression and expectation dependence","authors":"Sudheesh K. Kattumannil,&nbsp;Deepesh Bhati,&nbsp;Isha Dewan","doi":"10.1007/s10463-025-00949-6","DOIUrl":"10.1007/s10463-025-00949-6","url":null,"abstract":"<div><p>In this paper, we propose nonparametric tests based on <i>U</i>-statistics for testing independence against two different classes of alternatives: positive regression dependence and positive expectation dependence. We obtain the asymptotic distribution of the test statistics both under the null and the alternative hypothesis. An extensive Monte Carlo simulation study is done to assess the finite sample performance of the proposed tests. The test procedures are illustrated using two data sets.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 2","pages":"327 - 349"},"PeriodicalIF":0.6,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147352845","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
Consistent group selection using global–local shrinkage priors in sparse normal linear regression 稀疏正态线性回归中使用全局-局部收缩先验的一致性组选择
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-26 DOI: 10.1007/s10463-025-00950-z
Sayantan Paul, Prasenjit Ghosh, Arijit Chakrabarti
{"title":"Consistent group selection using global–local shrinkage priors in sparse normal linear regression","authors":"Sayantan Paul,&nbsp;Prasenjit Ghosh,&nbsp;Arijit Chakrabarti","doi":"10.1007/s10463-025-00950-z","DOIUrl":"10.1007/s10463-025-00950-z","url":null,"abstract":"<div><p>Consider a high-dimensional normal linear regression model when the candidate regressors are inherently grouped. Our interest is in grouped variable selection and estimation of parameters in a sparse asymptotic regime. We model the grouped regression coefficients by a broad class of “global–local\" shrinkage priors which can also be seen as a generalization of the standard g-prior with a shrinkage parameter. The global shrinkage parameter is either treated as a tuning parameter or in an empirical Bayes estimator or full Bayesian way. We consider a group selection rule, namely the Half-Thresholding rule and an estimator using that. Our methods are to enjoy the oracle property asymptotically in that they achieve variable selection consistency and optimal rate of estimation under a block-orthogonal design. These are the first theoretical results of their kind using such priors in this context. In simulation study, our rules perform favorably to many existing methods.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 3","pages":"399 - 433"},"PeriodicalIF":0.6,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924107","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
Variable selection via penalized ridge regression with error-prone variables 变量选择通过惩罚岭回归与容易出错的变量
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-26 DOI: 10.1007/s10463-025-00940-1
Li-Pang Chen
{"title":"Variable selection via penalized ridge regression with error-prone variables","authors":"Li-Pang Chen","doi":"10.1007/s10463-025-00940-1","DOIUrl":"10.1007/s10463-025-00940-1","url":null,"abstract":"<div><p>Variable selection is a fundamental topic in statistical analysis and data science. Regularization methods have been widely employed to identify informative variables related to the response. However, challenges such as collinearity and measurement error often arise in real-world datasets. In this paper, we address variable selection and estimation for linear models and focus parameters. To simultaneously handle collinearity and measurement error, we propose a valid correction strategy for error-prone continuous, binary, and discrete covariates, and develop a penalized ridge regression method to perform variable selection and estimation. We establish the theoretical properties of the proposed method, including variable selection consistency and asymptotic normality. Numerical studies are conducted to evaluate its performance, and the results demonstrate that the proposed method outperforms existing approaches.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 2","pages":"225 - 261"},"PeriodicalIF":0.6,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147352791","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
Quadratic functional estimation from observations with multiplicative measurement error 二次泛函估计从观测乘测量误差
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-23 DOI: 10.1007/s10463-025-00936-x
Fabienne Comte, Jan Johannes, Bianca Neubert
{"title":"Quadratic functional estimation from observations with multiplicative measurement error","authors":"Fabienne Comte,&nbsp;Jan Johannes,&nbsp;Bianca Neubert","doi":"10.1007/s10463-025-00936-x","DOIUrl":"10.1007/s10463-025-00936-x","url":null,"abstract":"<div><p>We consider the nonparametric estimation of the value of a quadratic functional evaluated at the density of a strictly positive random variable <i>X</i> based on an iid. sample from an observation <i>Y</i> of <i>X</i> corrupted by an independent multiplicative error <i>U</i>. Quadratic functionals of the density covered are the <span>({mathbb{L}^{2} })</span>-norm of the density and its derivatives or the survival function. We construct a fully data-driven estimator when the error density is known. The plug-in estimator is based on a density estimation combining the estimation of the Mellin transform of the <i>Y</i> density and a spectral cut-off regularized inversion of the Mellin transform of the error density. The main issue is the data-driven choice of the cut-off parameter using a Goldenshluger–Lepski-method. We discuss conditions under which the fully data-driven estimator attains oracle-rates up to logarithmic deteriorations. We compute convergence rates under classical smoothness assumptions and illustrate them by a simulation study.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 1","pages":"1 - 41"},"PeriodicalIF":0.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071379","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
Central limit theorems for vector-valued composite functionals with smoothing and applications 具有平滑的向量值复合泛函的中心极限定理及其应用
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-21 DOI: 10.1007/s10463-025-00934-z
Huihui Chen, Darinka Dentcheva, Yang Lin, Gregory J. Stock
{"title":"Central limit theorems for vector-valued composite functionals with smoothing and applications","authors":"Huihui Chen,&nbsp;Darinka Dentcheva,&nbsp;Yang Lin,&nbsp;Gregory J. Stock","doi":"10.1007/s10463-025-00934-z","DOIUrl":"10.1007/s10463-025-00934-z","url":null,"abstract":"<div><p>This paper focuses on vector-valued composite functionals, which may be nonlinear in probability. Our goal is establishing central limit theorems for these functionals when employed by mixed estimators. Our study is relevant to the evaluation and comparison of risk in decision-making contexts and extends to functionals that arise in machine learning. A generalized family of composite risk functionals is presented, which encompasses coherent risk measures, including systemic risk. The paper makes two main contributions. First, we analyze vector-valued functionals and provide a framework for evaluating high-dimensional risks. This enables comparison of multiple risk measures and supports estimation and asymptotic analysis of systemic risk and its optimal value in decision-making. Second, we derive new central limit theorems for optimized composite functionals using mixed estimators, including empirical and smoothed types. We give verifiable conditions for central limit formulae and demonstrate their applicability to several risk measures.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"77 5","pages":"821 - 852"},"PeriodicalIF":0.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923247","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
Inference in models with omitted covariates: Cramér-type moderate deviations and applications to high-dimensional regression 在省略协变量的模型中的推断：cram<s:1>适度偏差及其在高维回归中的应用
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-17 DOI: 10.1007/s10463-025-00935-y
Rebecca M. Lewis, Heather S. Battey, Wen-Xin Zhou
{"title":"Inference in models with omitted covariates: Cramér-type moderate deviations and applications to high-dimensional regression","authors":"Rebecca M. Lewis,&nbsp;Heather S. Battey,&nbsp;Wen-Xin Zhou","doi":"10.1007/s10463-025-00935-y","DOIUrl":"10.1007/s10463-025-00935-y","url":null,"abstract":"<div><p>We study a score statistic for inference on an interest parameter in a linear model with omitted covariates, establishing Berry–Esseen and Cramér-type moderate deviation bounds on the associated normal approximation. This entails a coupling between well-behaved but unobservable random variables and observable ones to which standard results do not straightforwardly apply. The theory is of self-standing interest but also provides new insights on backwards reduction procedures used in high-dimensional regression. An example details how our results may be used to analyse the high-dimensional procedure proposed by Cox and Battey (<i>Proceedings of the National Academy of Sciences,</i> <b>114</b>, 8592–8595, 2017).</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 2","pages":"177 - 224"},"PeriodicalIF":0.6,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147352850","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
Robust empirical likelihood variable selection for the high dimensional single-index regression model 高维单指标回归模型的稳健经验似然变量选择
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-16 DOI: 10.1007/s10463-025-00938-9
Huybrechts F. Bindele, Olivia Atutey
{"title":"Robust empirical likelihood variable selection for the high dimensional single-index regression model","authors":"Huybrechts F. Bindele,&nbsp;Olivia Atutey","doi":"10.1007/s10463-025-00938-9","DOIUrl":"10.1007/s10463-025-00938-9","url":null,"abstract":"<div><p>A single-index regression model is considered, from which a robust and efficient inference about the model parameters is proposed. From a local linear approximation of the unknown regression function, such a function is estimated using the generalized signed-rank approach. Next considering the estimated function together with the estimating equation obtained from the generalized sign-rank objective function, a penalized empirical likelihood objective function of the index parameter is defined, from which its asymptotic distribution is established under mild regularity conditions. The performance of the proposed method is demonstrated via extensive Monte Carlo simulation experiments. The obtained simulation results are compared with those obtained from a normal approximation alternative and those obtained based on the least squares and least absolute deviations approaches. Finally, a real data example is given to illustrate the proposed methodology.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 1","pages":"93 - 113"},"PeriodicalIF":0.6,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071354","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
Exact two-sided confidence sets for a level set in simple linear regression 简单线性回归中水平集的精确双侧置信集
IF 0.6 4区 数学
Annals of the Institute of Statistical Mathematics Pub Date : 2025-07-15 DOI: 10.1007/s10463-025-00946-9
Fang Wan, Wei Liu, Frank Bretz
{"title":"Exact two-sided confidence sets for a level set in simple linear regression","authors":"Fang Wan,&nbsp;Wei Liu,&nbsp;Frank Bretz","doi":"10.1007/s10463-025-00946-9","DOIUrl":"10.1007/s10463-025-00946-9","url":null,"abstract":"<div><p>Regression modeling is the workhorse of statistics. It is realized in recent years that one important aim in regression analysis may be the estimation of a level set of the regression function. The published work on this has thus far focused mainly on nonparametric regression, especially on point estimation. In our previous work, we constructed exact upper and lower, but only conservative two-sided, confidence sets for a level set in linear regression. In this paper, exact two-sided confidence sets are constructed in simple linear regression. A simultaneity property of the exact two-sided confidence is also studied. An example is given to illustrate the method.</p></div>","PeriodicalId":55511,"journal":{"name":"Annals of the Institute of Statistical Mathematics","volume":"78 2","pages":"263 - 274"},"PeriodicalIF":0.6,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147352875","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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