{"title":"Bayesian inference in the framework of uncertainty theory","authors":"","doi":"10.1007/s12652-024-04785-z","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Bayesian inference is one of the important topics in modern statistics. The information of the parameter in Bayesian statistics which is regarded as some random variable will be updated by that of the posterior distribution. In other words, all the inferences in Bayesian statistics are based on the updated posterior information, which has been proven to be a very powerful technique. In this paper, we study the Bayesian inference in the framework of uncertainty theory based on the uncertain Bayesian rule developed by Lio and Kang in 2022. To be more precise, issues on the point estimation, credible intervals and hypothesis testing in Bayesian statistics under uncertain theory are explored, and one application of our method in an IQ test problem is also given in this paper.</p>","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ambient Intelligence and Humanized Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12652-024-04785-z","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Bayesian inference is one of the important topics in modern statistics. The information of the parameter in Bayesian statistics which is regarded as some random variable will be updated by that of the posterior distribution. In other words, all the inferences in Bayesian statistics are based on the updated posterior information, which has been proven to be a very powerful technique. In this paper, we study the Bayesian inference in the framework of uncertainty theory based on the uncertain Bayesian rule developed by Lio and Kang in 2022. To be more precise, issues on the point estimation, credible intervals and hypothesis testing in Bayesian statistics under uncertain theory are explored, and one application of our method in an IQ test problem is also given in this paper.
期刊介绍：
The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to):
Pervasive/Ubiquitous Computing and Applications
Cognitive wireless sensor network
Embedded Systems and Software
Mobile Computing and Wireless Communications
Next Generation Multimedia Systems
Security, Privacy and Trust
Service and Semantic Computing
Advanced Networking Architectures
Dependable, Reliable and Autonomic Computing
Embedded Smart Agents
Context awareness, social sensing and inference
Multi modal interaction design
Ergonomics and product prototyping
Intelligent and self-organizing transportation networks & services
Healthcare Systems
Virtual Humans & Virtual Worlds
Wearables sensors and actuators
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