{"title":"确定潜在维度数量并评估其可靠性的集合方法","authors":"Asana Neishabouri, Michel C. Desmarais","doi":"10.1080/03610918.2024.2328166","DOIUrl":null,"url":null,"abstract":"Determining the number of latent dimensions (LD) of a data set is a ubiquitous problem, for which numerous methods have been developed. We compare some of the most effective ones on synthetic data,...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"13 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An ensemble approach to determine the number of latent dimensions and assess its reliability\",\"authors\":\"Asana Neishabouri, Michel C. Desmarais\",\"doi\":\"10.1080/03610918.2024.2328166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining the number of latent dimensions (LD) of a data set is a ubiquitous problem, for which numerous methods have been developed. We compare some of the most effective ones on synthetic data,...\",\"PeriodicalId\":55240,\"journal\":{\"name\":\"Communications in Statistics-Simulation and Computation\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Statistics-Simulation and Computation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/03610918.2024.2328166\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Statistics-Simulation and Computation","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/03610918.2024.2328166","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
An ensemble approach to determine the number of latent dimensions and assess its reliability
Determining the number of latent dimensions (LD) of a data set is a ubiquitous problem, for which numerous methods have been developed. We compare some of the most effective ones on synthetic data,...
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The Simulation and Computation series intends to publish papers that make theoretical and methodological advances relating to computational aspects of Probability and Statistics. Simulational assessment and comparison of the performance of statistical and probabilistic methods will also be considered for publication. Papers stressing graphical methods, resampling and other computationally intensive methods will be particularly relevant. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership.
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