EMアルゴリズムの基礎

• 田川 憲男

  東京都立大学大学院工学研究科

書誌事項

タイトル別名

• Fundamentals of the EM Algorithm

抄録

The EM (Expectation-Maximization) algorithm is a general-purpose stable procedure for maximum likelihood estimation in a wide variety of situations described as incomplete-data problem. Incomplete- data problems where the EM algorithm has been succesfully applied include not only evidently incomplete- data situations, for example, there are missing data, grouped observations, but also a whole variety of situations where the incompleteness of the data is not natural or evident.<BR>In this article, at first, I summarize maximum likelihood estimation and formulation of the EM algorithm. Subsequently, I briefly mention the properties of the EM algorithm, and two applications where the typical probablistic models are assumed. Lastly, I introduce some problems, which arise from applying the EM algorithm to the complex situations, and the examples of the solutions against them.

収録刊行物

• Japanese Journal of Medical Physics

  Japanese Journal of Medical Physics 19 (3), 148-161, 1999

  一般社団法人 日本医学物理学会

キーワード

• EM algorithm
• maximum likelihood estimation
• MAP estimation
• inite nor-mal mixture
• parametrci model

詳細情報

• CRID: 1390001204672528384
• NII論文ID: 10004572550
• NII書誌ID: AA11137895
• DOI: 10.11323/jjmp1992.19.3_148
• ISSN: 21869855
• ISSN: 09188010
• Web Site: https://search.jamas.or.jp/link/ui/2000149905
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可