{"title":"On the Certainty of an Inductive Inference: The Binomial Case","authors":"Frank Tuyl, Richard Gerlach, K. Mengersen","doi":"10.1214/23-sts913","DOIUrl":"https://doi.org/10.1214/23-sts913","url":null,"abstract":"","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141046214","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}
Eric-Jan Wagenmakers, Sandy L. Zabell, Q. F. Gronau
{"title":"J. B. S. Haldane’s Rule of Succession","authors":"Eric-Jan Wagenmakers, Sandy L. Zabell, Q. F. Gronau","doi":"10.1214/23-sts912","DOIUrl":"https://doi.org/10.1214/23-sts912","url":null,"abstract":"","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141058519","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}
Statistical SciencePub Date : 2024-05-01Epub Date: 2024-05-05DOI: 10.1214/23-sts900
Chuji Luo, Michael J Daniels
{"title":"Variable Selection Using Bayesian Additive Regression Trees.","authors":"Chuji Luo, Michael J Daniels","doi":"10.1214/23-sts900","DOIUrl":"10.1214/23-sts900","url":null,"abstract":"<p><p>Variable selection is an important statistical problem. This problem becomes more challenging when the candidate predictors are of mixed type (e.g. continuous and binary) and impact the response variable in nonlinear and/or non-additive ways. In this paper, we review existing variable selection approaches for the Bayesian additive regression trees (BART) model, a nonparametric regression model, which is flexible enough to capture the interactions between predictors and nonlinear relationships with the response. An emphasis of this review is on the ability to identify relevant predictors. We also propose two variable importance measures which can be used in a permutation-based variable selection approach, and a backward variable selection procedure for BART. We introduce these variations as a way of illustrating limitations and opportunities for improving current approaches and assess these via simulations.</p>","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11395240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300349","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}
{"title":"A Conversation with Guido W. Imbens","authors":"Fabrizia Mealli, Julie Holland Mortimer","doi":"10.1214/23-sts906","DOIUrl":"https://doi.org/10.1214/23-sts906","url":null,"abstract":"","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141053399","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}
{"title":"In Conversation with Sir David Spiegelhalter and Professor Sylvia Richardson","authors":"Bhramar Mukherjee","doi":"10.1214/23-sts897","DOIUrl":"https://doi.org/10.1214/23-sts897","url":null,"abstract":"","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465098","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}
Erik Štrumbelj, A. Bouchard-Côté, J. Corander, Andrew Gelman, H. Rue, Lawrence Murray, Henri Pesonen, M. Plummer, A. Vehtari
{"title":"Past, Present and Future of Software for Bayesian Inference","authors":"Erik Štrumbelj, A. Bouchard-Côté, J. Corander, Andrew Gelman, H. Rue, Lawrence Murray, Henri Pesonen, M. Plummer, A. Vehtari","doi":"10.1214/23-sts907","DOIUrl":"https://doi.org/10.1214/23-sts907","url":null,"abstract":". Software tools for Bayesian inference have undergone rapid evolution in the past three decades, following popularisation of the first generation MCMC-sampler implementations. More recently, exponential growth in the number of users has been stimulated both by the active development of new packages by the machine learning community and popularity of specialist software for particular applications. This review aims to summarize the most popular software and provide a useful map for a reader to navigate the world of Bayesian computation. We anticipate a vigorous continued development of algorithms and corresponding software in multiple research fields, such as probabilistic programming, likelihood-free inference, and Bayesian neural networks, which will further broaden the possibilities for employing the Bayesian paradigm in exciting applications.","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464818","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}
{"title":"Editorial: Bayesian Computations in the 21st Century","authors":"Christian P. Robert, Dennis Prangle","doi":"10.1214/23-sts920","DOIUrl":"https://doi.org/10.1214/23-sts920","url":null,"abstract":"","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139966568","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}
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