Statistical Science最新文献_第4页

High-Performance Statistical Computing in the Computing Environments of the 2020s. 2020 年代计算环境中的高性能统计计算。

IF 3.9 1区数学

Statistical Science Pub Date : 2022-11-01 Epub Date: 2022-10-13 DOI: 10.1214/21-sts835

Seyoon Ko, Hua Zhou, Jin J Zhou, Joong-Ho Won

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引用次数: 0

Comments on Confidence as Likelihood by Pawitan and Lee in Statistical Science, November 2021 Pawitan和Lee在《统计科学》杂志上对置信度作为可能性的评论，2021年11月

IF 5.7 1区数学

Statistical Science Pub Date : 2022-11-01 DOI: 10.1214/22-sts862

M. Lavine, J. F. Bjørnstad

引用次数: 0

A Regression Perspective on Generalized Distance Covariance and the Hilbert–Schmidt Independence Criterion 广义距离协方差与Hilbert–Schmidt独立性准则的回归分析

IF 5.7 1区数学

Statistical Science Pub Date : 2022-11-01 DOI: 10.1214/21-sts841

Dominic Edelmann, J. Goeman

引用次数: 2

Approximate Confidence Intervals for a Binomial p—Once Again 二项p的近似置信区间

IF 5.7 1区数学

Statistical Science Pub Date : 2022-11-01 DOI: 10.1214/21-sts837

Per Gösta Andersson

{"title":"Approximate Confidence Intervals for a Binomial p—Once Again","authors":"Per Gösta Andersson","doi":"10.1214/21-sts837","DOIUrl":"https://doi.org/10.1214/21-sts837","url":null,"abstract":"The problem of constructing a reasonably simple yet well behaved confidence interval for a binomial parameter p is old but still fascinating and surprisingly complex. During the last century many alternatives to the poorly behaved standard Wald interval have been suggested. It seems though that the Wald interval is still much in use in spite of many efforts over the years through publications to point out its deficiencies. This paper constitutes yet another attempt to provide an alternative and it builds on a special case of a general technique for adjusted intervals primarily based on Wald type statistics. The main idea is to construct an approximate pivot with uncorrelated, or nearly uncorrelated, components. The resulting (AN) Andersson-Nerman interval, as well as a modification thereof, is compared with the well renowned Wilson and AC (Agresti-Coull) intervals and the subsequent discussion will in itself hopefully shed some new light on this seemingly elementary interval estimation situation. Generally, an alternative to the Wald interval is to be judged not only by performance, its expression should also indicate why we will obtain a better behaved interval. It is argued that the well-behaved AN interval meets this requirement.","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41959851","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: 1

Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors 使用校准良好的零偏好先验解释p值和置信区间

IF 5.7 1区数学

Statistical Science Pub Date : 2022-11-01 DOI: 10.1214/21-sts833

M. Fay, M. Proschan, E. Brittain, R. Tiwari

引用次数: 2

A Probabilistic View on Predictive Constructions for Bayesian Learning 贝叶斯学习预测结构的概率观

IF 5.7 1区数学

Statistical Science Pub Date : 2022-08-14 DOI: 10.1214/23-sts884

P. Berti, E. Dreassi, F. Leisen, P. Rigo, L. Pratelli

引用次数: 0

A Conversation with Stephen Portnoy 对话斯蒂芬波特诺伊

IF 5.7 1区数学

Statistical Science Pub Date : 2022-08-01 DOI: 10.1214/21-sts845

Xu He, Xi-bin Shao

{"title":"A Conversation with Stephen Portnoy","authors":"Xu He, Xi-bin Shao","doi":"10.1214/21-sts845","DOIUrl":"https://doi.org/10.1214/21-sts845","url":null,"abstract":"Steve Portnoy was born in Kankakee, Illinois in 1942. He did his undergraduate studies in mathematics at Massachusetts Institute of Technology, and then earned a master’s degree and a Ph.D. degree from the statistics department at Stanford University in 1966 and 1969, respectively. Steve Portnoy has had a distinguished career and is widely recognized as a preeminent mathematical statistician. He has made pioneering and influential contributions in several areas in statistics, including asymptotic theory, robust statistics, quantile regression, and statistics in biology. He has published more than 100 research articles. He is a former co-editor of Journal of the American Statistical Association, Theory and Methods, an elected fellow of American Statistical Association (ASA), Institute of Mathematical Statistics (IMS) and American Association for the Advancement of Science (AAAS). Steve’s professional positions have included being on the faculty of the Department of Statistics at Harvard University and the University of Illinois at Urbana-Champaign for more than 30 years. He was a founding member of the Department of Statistics at the University of Illinois in 1985 and served as the division chair (1983-1985) for Statistics Program in the Mathematics department before the Statistics department was established.","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44370837","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

Intention-to-Treat Comparisons in Randomized Trials 随机试验中的意向治疗比较

IF 5.7 1区数学

Statistical Science Pub Date : 2022-08-01 DOI: 10.1214/21-sts830

R. Prentice, A. Aragaki

引用次数: 4

Computing Bayes: From Then ‘Til Now 计算贝叶斯：从那时到现在

IF 5.7 1区数学

Statistical Science Pub Date : 2022-08-01 DOI: 10.1214/22-STS876

G. Martin, David T. Frazier, C. Robert

引用次数: 7

Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring. 从动态模型中学习和预测 COVID-19 患者监测。

IF 3.9 1区数学

Statistical Science Pub Date : 2022-05-01 Epub Date: 2022-05-16 DOI: 10.1214/22-sts861

Zitong Wang, Mary Grace Bowring, Antony Rosen, Brian Garibaldi, Scott Zeger, Akihiko Nishimura

{"title":"Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring.","authors":"Zitong Wang, Mary Grace Bowring, Antony Rosen, Brian Garibaldi, Scott Zeger, Akihiko Nishimura","doi":"10.1214/22-sts861","DOIUrl":"10.1214/22-sts861","url":null,"abstract":"COVID-19 has challenged health systems to learn how to learn. This paper describes the context, methods and challenges for learning to improve COVID-19 care at one academic health center. Challenges to learning include: (1) choosing a right clinical target; (2) designing methods for accurate predictions by borrowing strength from prior patients' experiences; (3) communicating the methodology to clinicians so they understand and trust it; (4) communicating the predictions to the patient at the moment of clinical decision; and (5) continuously evaluating and revising the methods so they adapt to changing patients and clinical demands. To illustrate these challenges, this paper contrasts two statistical modeling approaches - prospective longitudinal models in common use and retrospective analogues complementary in the COVID-19 context - for predicting future biomarker trajectories and major clinical events. The methods are applied to and validated on a cohort of 1,678 patients who were hospitalized with COVID-19 during the early months of the pandemic. We emphasize graphical tools to promote physician learning and inform clinical decision making.","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":"37 2","pages":"251-265"},"PeriodicalIF":3.9,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198065/pdf/nihms-1844199.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9864796","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