자료유형 | E-Book |
---|---|
개인저자 | Wang, Xiaomu. |
단체저자명 | The Ohio State University. Statistics. |
서명/저자사항 | Robust Bayes in Hierarchical Modeling and Empirical Bayes Analysis in Multivariate Estimation. |
발행사항 | [S.l.] : The Ohio State University., 2015 |
발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2015 |
형태사항 | 99 p. |
소장본 주기 | School code: 0168. |
ISBN | 9780438097315 |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Berliner L. Mark. |
요약 | With the modern development of statistical data analysis, the data volume increases and the data dimension increases correspondingly. This thesis investigates two classic Bayes problems: robust Bayes analysis in hierarchical modeling and empiric |
요약 | In Bayesian analysis, it is difficult to develop a single prior to completely and fully quantify our prior information. Thereby, o-contamination classes have become popular models of the uncertainty in prior distributions. For the first part of |
요약 | When a class of priors is assumed in Bayesian analysis, it is vital to consider a decision rule corresponding to this class. In a multivariate estimation setting, for the second part of this thesis, I focus on research to find a compromise betwe |
일반주제명 | Statistics. |
언어 | 영어 |
기본자료 저록 | Dissertation Abstracts International79-10B(E). Dissertation Abstract International |
대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T15000267 |