Pub Date : 2023-10-02DOI: 10.1080/00401706.2023.2262893
Irvanal Haq, Nila Lestari
{"title":"Statistical GenomicsBrooke Fridley and Xuefeng Wang, New York, NY: Humana, 2023, 377 pp., EUR 169.99, ISBN 978-1-0716-2986-4 (eBook)","authors":"Irvanal Haq, Nila Lestari","doi":"10.1080/00401706.2023.2262893","DOIUrl":"https://doi.org/10.1080/00401706.2023.2262893","url":null,"abstract":"","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135948485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.1080/00401706.2023.2262898
Stan Lipovetsky
{"title":"Mathematics of The Big Four Casino Table Games: Blackjack, Baccarat, Craps, & RouletteMark Bollman, Boca Raton, FL: CRC Press/Chapman & Hall, Taylor & Francis Group, 2021, xi +353 pp., 43 B/W illustrations, $ 31.16 (pbk), ISBN 9780367740900","authors":"Stan Lipovetsky","doi":"10.1080/00401706.2023.2262898","DOIUrl":"https://doi.org/10.1080/00401706.2023.2262898","url":null,"abstract":"","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135948475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.1080/00401706.2023.2262889
Stan Lipovetsky
{"title":"Luck, Logic, and White Lies: The Mathematics of Games; 2nd ed.Jörg Bewersdorff, translated by David Kramer, Boca Raton, FL: A.K. Peters/CRC Press, Taylor & Francis Group, 2021, xx + 548 pp., $ 47.96 (pbk), ISBN 9780367548414","authors":"Stan Lipovetsky","doi":"10.1080/00401706.2023.2262889","DOIUrl":"https://doi.org/10.1080/00401706.2023.2262889","url":null,"abstract":"","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135948481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-13DOI: 10.1080/00401706.2023.2257765
John C. Yannotty, Thomas J. Santner, Richard J. Furnstahl, Matthew T. Pratola
In modern computer experiment applications, one often encounters the situation where various models of a physical system are considered, each implemented as a simulator on a computer. An important question in such a setting is determining the best simulator, or the best combination of simulators, to use for prediction and inference. Bayesian model averaging (BMA) and stacking are two statistical approaches used to account for model uncertainty by aggregating a set of predictions through a simple linear combination or weighted average. Bayesian model mixing (BMM) extends these ideas to capture the localized behavior of each simulator by defining input-dependent weights. One possibility is to define the relationship between inputs and the weight functions using a flexible non-parametric model that learns the local strengths and weaknesses of each simulator. This paper proposes a BMM model based on Bayesian Additive Regression Trees (BART). The proposed methodology is applied to combine predictions from Effective Field Theories (EFTs) associated with a motivating nuclear physics application. Supplementary Material is available online. Source code is available at https://github.com/jcyannotty/OpenBT.
{"title":"Model Mixing Using Bayesian Additive Regression Trees","authors":"John C. Yannotty, Thomas J. Santner, Richard J. Furnstahl, Matthew T. Pratola","doi":"10.1080/00401706.2023.2257765","DOIUrl":"https://doi.org/10.1080/00401706.2023.2257765","url":null,"abstract":"In modern computer experiment applications, one often encounters the situation where various models of a physical system are considered, each implemented as a simulator on a computer. An important question in such a setting is determining the best simulator, or the best combination of simulators, to use for prediction and inference. Bayesian model averaging (BMA) and stacking are two statistical approaches used to account for model uncertainty by aggregating a set of predictions through a simple linear combination or weighted average. Bayesian model mixing (BMM) extends these ideas to capture the localized behavior of each simulator by defining input-dependent weights. One possibility is to define the relationship between inputs and the weight functions using a flexible non-parametric model that learns the local strengths and weaknesses of each simulator. This paper proposes a BMM model based on Bayesian Additive Regression Trees (BART). The proposed methodology is applied to combine predictions from Effective Field Theories (EFTs) associated with a motivating nuclear physics application. Supplementary Material is available online. Source code is available at https://github.com/jcyannotty/OpenBT.","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134989786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-28DOI: 10.1080/00401706.2023.2252476
Robert W. Mee, H. Li
{"title":"Inference for the Optimum using Linear Regression Models with Discrete Inputs","authors":"Robert W. Mee, H. Li","doi":"10.1080/00401706.2023.2252476","DOIUrl":"https://doi.org/10.1080/00401706.2023.2252476","url":null,"abstract":"","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44956453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.1080/00401706.2023.2242413
Guanqi Fang, Rong Pan
{"title":"A Class of Hierarchical Multivariate Wiener Processes for Modeling Dependent Degradation Data","authors":"Guanqi Fang, Rong Pan","doi":"10.1080/00401706.2023.2242413","DOIUrl":"https://doi.org/10.1080/00401706.2023.2242413","url":null,"abstract":"","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43926238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-26DOI: 10.1080/00401706.2023.2241523
X. Ye, Jiaxiang Cai, L. Tang, Z. Ye
{"title":"Statistical Modeling of the Effectiveness of Preventive Maintenance for Repairable Systems","authors":"X. Ye, Jiaxiang Cai, L. Tang, Z. Ye","doi":"10.1080/00401706.2023.2241523","DOIUrl":"https://doi.org/10.1080/00401706.2023.2241523","url":null,"abstract":"","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49473789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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