首页    期刊浏览 2024年09月19日 星期四
登录注册

文章基本信息

  • 标题:Full Bayesian Significance Test Applied to Multivariate Normal Structure Models
  • 本地全文:下载
  • 作者:M. LAURETTO ; C. A. B. PEREIRA ; J. M. STERN
  • 期刊名称:Brazilian Journal of Probability and Statistics
  • 印刷版ISSN:0103-0752
  • 出版年度:2003
  • 卷号:17
  • 期号:2
  • 页码:147-168
  • 出版社:Brazilian Statistical Association
  • 摘要:The Full Bayesian Significance Test (FBST) for precise hy-potheses is applied to a Multivariate Normal Structure (MNS) model. Inthe FBST we compute the evidence against the precise hypothesis. This evi-dence is the probability of the Highest Relative Surprise Set (HRSS) tangentto the sub-manifold (of the parameter space) that defines the null hypothesis.The MNS mo del we present appears when testing equivalence conditions forgenetic expression measurements, using micro-array technology
  • 关键词:Credibility; evidence; full Bayesian significance test; relative;surprise; structural mo dels for multivariate normals
国家哲学社会科学文献中心版权所有