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Journal of the Royal Statistical Society Series B-Statistical Methodology最新文献

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Correction to: Sensitivity Analysis for Inverse Probability Weighting Estimators via the Percentile Bootstrap 修正:通过百分位Bootstrap对逆概率加权估计的敏感性分析
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-08-05 DOI: 10.1093/jrsssb/qkad079
{"title":"Correction to: Sensitivity Analysis for Inverse Probability Weighting Estimators via the Percentile Bootstrap","authors":"","doi":"10.1093/jrsssb/qkad079","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad079","url":null,"abstract":"","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"1 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90507150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Autoregressive optimal transport models. 自回归最优运输模型。
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-07-01 DOI: 10.1093/jrsssb/qkad051
Changbo Zhu, Hans-Georg Müller
{"title":"Autoregressive optimal transport models.","authors":"Changbo Zhu,&nbsp;Hans-Georg Müller","doi":"10.1093/jrsssb/qkad051","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad051","url":null,"abstract":"<p><p>Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field of distributional data analysis. To quantify such distributional time series, we propose a class of intrinsic autoregressive models that operate in the space of optimal transport maps. The autoregressive transport models that we introduce here are based on regressing optimal transport maps on each other, where predictors can be transport maps from an overall barycenter to a current distribution or transport maps between past consecutive distributions of the distributional time series. Autoregressive transport models and their associated distributional regression models specify the link between predictor and response transport maps by moving along geodesics in Wasserstein space. These models emerge as natural extensions of the classical autoregressive models in Euclidean space. Unique stationary solutions of autoregressive transport models are shown to exist under a geometric moment contraction condition of Wu & Shao [(2004) Limit theorems for iterated random functions. <i>Journal of Applied Probability 41</i>, 425-436)], using properties of iterated random functions. We also discuss an extension to a varying coefficient model for first-order autoregressive transport models. In addition to simulations, the proposed models are illustrated with distributional time series of house prices across U.S. counties and annual summer temperature distributions.</p>","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"85 3","pages":"1012-1033"},"PeriodicalIF":5.8,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/69/84/qkad051.PMC10376456.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9910306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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: 12
Testing homogeneity: the trouble with sparse functional data. 测试同质性:稀疏函数数据的麻烦。
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-07-01 DOI: 10.1093/jrsssb/qkad021
Changbo Zhu, Jane-Ling Wang
{"title":"Testing homogeneity: the trouble with sparse functional data.","authors":"Changbo Zhu,&nbsp;Jane-Ling Wang","doi":"10.1093/jrsssb/qkad021","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad021","url":null,"abstract":"<p><p>Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging for sparsely measured functional data and show what can be done for such data. In particular, we show that testing the marginal homogeneity based on point-wise distributions is feasible under some mild constraints and propose a new two-sample statistic that works well with both intensively and sparsely measured functional data. The proposed test statistic is formulated upon energy distance, and the convergence rate of the test statistic to its population version is derived along with the consistency of the associated permutation test. The aptness of our method is demonstrated on both synthetic and real data sets.</p>","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"85 3","pages":"705-731"},"PeriodicalIF":5.8,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/48/e2/qkad021.PMC10376451.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9964440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
On the causal interpretation of randomised interventional indirect effects 关于随机介入间接效应的因果解释
1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-06-28 DOI: 10.1093/jrsssb/qkad066
Caleb H Miles
{"title":"On the causal interpretation of randomised interventional indirect effects","authors":"Caleb H Miles","doi":"10.1093/jrsssb/qkad066","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad066","url":null,"abstract":"Abstract Identification of standard mediated effects such as the natural indirect effect relies on heavy causal assumptions. By circumventing such assumptions, so-called randomised interventional indirect effects have gained popularity in the mediation literature. Here, I introduce properties one might demand of an indirect effect measure in order for it to have a true mediational interpretation. For instance, the sharp null criterion requires an indirect effect measure to be null whenever no individual-level indirect effect exists. I show that without stronger assumptions, randomised interventional indirect effects do not satisfy such criteria. I additionally discuss alternative causal interpretations of such effects.","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135155944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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: 3
Two-stage estimation and bias-corrected empirical likelihood in a partially linear single-index varying-coefficient model 部分线性单指标变系数模型的两阶段估计和偏差校正经验似然
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-06-27 DOI: 10.1093/jrsssb/qkad060
L. Xue
{"title":"Two-stage estimation and bias-corrected empirical likelihood in a partially linear single-index varying-coefficient model","authors":"L. Xue","doi":"10.1093/jrsssb/qkad060","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad060","url":null,"abstract":"\u0000 The estimation and empirical likelihood (EL) of the parameters of interest in a partially linear single-index varying-coefficient model are studied. A two-stage method is presented to estimate the regression parameters and the coefficient functions. The asymptotic distributions of the proposed estimators are obtained. Meanwhile, a bias-corrected EL ratio for the regression parameters is proposed. It is shown that the ratio is asymptotically standard chi-squared. The result can be directly used to construct the EL confidence regions of the regression parameters. Simulation studies are carried out to evaluate the finite sample behaviour of the proposed method. An application example of a real data set is given.","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"31 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75007076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 for the Markov property in time series via deep conditional generative learning. 通过深度条件生成学习测试时间序列中的马尔可夫性质。
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-06-23 eCollection Date: 2023-09-01 DOI: 10.1093/jrsssb/qkad064
Yunzhe Zhou, Chengchun Shi, Lexin Li, Qiwei Yao
{"title":"Testing for the Markov property in time series via deep conditional generative learning.","authors":"Yunzhe Zhou, Chengchun Shi, Lexin Li, Qiwei Yao","doi":"10.1093/jrsssb/qkad064","DOIUrl":"10.1093/jrsssb/qkad064","url":null,"abstract":"<p><p>The Markov property is widely imposed in analysis of time series data. Correspondingly, testing the Markov property, and relatedly, inferring the order of a Markov model, are of paramount importance. In this article, we propose a nonparametric test for the Markov property in high-dimensional time series via deep conditional generative learning. We also apply the test sequentially to determine the order of the Markov model. We show that the test controls the type-I error asymptotically, and has the power approaching one. Our proposal makes novel contributions in several ways. We utilise and extend state-of-the-art deep generative learning to estimate the conditional density functions, and establish a sharp upper bound on the approximation error of the estimators. We derive a doubly robust test statistic, which employs a nonparametric estimation but achieves a parametric convergence rate. We further adopt sample splitting and cross-fitting to minimise the conditions required to ensure the consistency of the test. We demonstrate the efficacy of the test through both simulations and the three data applications.</p>","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"85 4","pages":"1204-1222"},"PeriodicalIF":5.8,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41140853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Normalised latent measure factor models 归一化潜在测量因子模型
1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-06-23 DOI: 10.1093/jrsssb/qkad062
Mario Beraha, Jim E Griffin
{"title":"Normalised latent measure factor models","authors":"Mario Beraha, Jim E Griffin","doi":"10.1093/jrsssb/qkad062","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad062","url":null,"abstract":"Abstract We propose a methodology for modelling and comparing probability distributions within a Bayesian nonparametric framework. Building on dependent normalised random measures, we consider a prior distribution for a collection of discrete random measures where each measure is a linear combination of a set of latent measures, interpretable as characteristic traits shared by different distributions, with positive random weights. The model is nonidentified and a method for postprocessing posterior samples to achieve identified inference is developed. This uses Riemannian optimisation to solve a nontrivial optimisation problem over a Lie group of matrices. The effectiveness of our approach is validated on simulated data and in two applications to two real-world data sets: school student test scores and personal incomes in California. Our approach leads to interesting insights for populations and easily interpretable posterior inference.","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136000276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Strategic two-sample test via the two-armed bandit process 通过双臂盗匪过程进行战略双样本检验
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-06-14 DOI: 10.1093/jrsssb/qkad061
Zengjing Chen, Xiaodong Yan, Guodong Zhang
{"title":"Strategic two-sample test via the two-armed bandit process","authors":"Zengjing Chen, Xiaodong Yan, Guodong Zhang","doi":"10.1093/jrsssb/qkad061","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad061","url":null,"abstract":"\u0000 This study aims to improve the power of two-sample tests by analysing whether the difference between two population parameters is larger than a prespecified positive equivalence margin. The classic test statistic treats the original data as exchangeable, while the proposed test statistic breaks the structure and proposes employing a two-armed bandit process to strategically integrate the data and thus a strategy-specific test statistic is constructed by combining the classic CLT with the law of large numbers. The developed asymptotic theory is investigated by using nonlinear limit theory in a larger probability space and relates to the ‘strategic CLT’ with a clearly defined density function. The asymptotic distribution demonstrates that the proposed statistic is more concentrated under the null hypothesis and less concentrated under the alternative than the classic CLT, thereby enhancing the testing power. Simulation studies provide supporting evidence for the theoretical results and portray a more powerful performance when using finite samples. A real example is also added for illustration.","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"113 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79323502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Quasi-Newton updating for large-scale distributed learning 大规模分布式学习的准牛顿更新
1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-06-10 DOI: 10.1093/jrsssb/qkad059
Shuyuan Wu, Danyang Huang, Hansheng Wang
{"title":"Quasi-Newton updating for large-scale distributed learning","authors":"Shuyuan Wu, Danyang Huang, Hansheng Wang","doi":"10.1093/jrsssb/qkad059","DOIUrl":"https://doi.org/10.1093/jrsssb/qkad059","url":null,"abstract":"Abstract Distributed computing is critically important for modern statistical analysis. Herein, we develop a distributed quasi-Newton (DQN) framework with excellent statistical, computation, and communication efficiency. In the DQN method, no Hessian matrix inversion or communication is needed. This considerably reduces the computation and communication complexity of the proposed method. Notably, related existing methods only analyse numerical convergence and require a diverging number of iterations to converge. However, we investigate the statistical properties of the DQN method and theoretically demonstrate that the resulting estimator is statistically efficient over a small number of iterations under mild conditions. Extensive numerical analyses demonstrate the finite sample performance.","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135006257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Correction to: Autoregressive optimal transport models. 更正：自回归最优运输模型。
IF 5.8 1区 数学
Journal of the Royal Statistical Society Series B-Statistical Methodology Pub Date : 2023-05-31 eCollection Date: 2023-07-01 DOI: 10.1093/jrsssb/qkad057
{"title":"Correction to: Autoregressive optimal transport models.","authors":"","doi":"10.1093/jrsssb/qkad057","DOIUrl":"10.1093/jrsssb/qkad057","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1093/jrsssb/qkad051.].</p>","PeriodicalId":49982,"journal":{"name":"Journal of the Royal Statistical Society Series B-Statistical Methodology","volume":"85 3","pages":"1035"},"PeriodicalIF":5.8,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/81/e7/qkad057.PMC10376444.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9888781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
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