{"title":"通过稳健性诱导变换实现稀疏偏最小二乘法的优雅稳健化","authors":"Sven Serneels, Luca Insolia, Tim Verdonck","doi":"10.1080/02331888.2024.2313507","DOIUrl":null,"url":null,"abstract":"Robust alternatives exist for many statistical estimators. State-of-the-art robust methods are fine-tuned to optimize the balance between statistical efficiency and robustness. The resulting estima...","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"1 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Elegant robustification of sparse partial least squares by robustness-inducing transformations\",\"authors\":\"Sven Serneels, Luca Insolia, Tim Verdonck\",\"doi\":\"10.1080/02331888.2024.2313507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Robust alternatives exist for many statistical estimators. State-of-the-art robust methods are fine-tuned to optimize the balance between statistical efficiency and robustness. The resulting estima...\",\"PeriodicalId\":54358,\"journal\":{\"name\":\"Statistics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/02331888.2024.2313507\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02331888.2024.2313507","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Elegant robustification of sparse partial least squares by robustness-inducing transformations
Robust alternatives exist for many statistical estimators. State-of-the-art robust methods are fine-tuned to optimize the balance between statistical efficiency and robustness. The resulting estima...
期刊介绍：
Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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