The Order of Degeneracy of Markov Chain Monte Carlo Method

• Kamatani Kengo

  Graduate School of Engineering Science, Osaka University

Abstract

Sometimes Markov chain Monte Carlo (MCMC) procedures work poorly. The identification of this inefficiency is important, but appropriate theoretical tools have not been investigated adequately. For this purpose, we propose the order of degeneracy, which measures the mixing property of an MCMC procedure. As an application, we consider major three sources of inefficiency, one being the fragility of the identification of parameters. We present a numerical simulation to show the effect of each source of inefficiency.

Journal

• JOURNAL OF THE JAPAN STATISTICAL SOCIETY

  JOURNAL OF THE JAPAN STATISTICAL SOCIETY 43 (2), 203-220, 2013

  THE JAPAN STATISTICAL SOCIETY

Keywords

• Bernstein–von Mises theorem
• Markov chain
• Monte Carlo method
• probit model

Details

• CRID: 1390001205286335744
• NII Article ID: 130004696125
• NII Article ID: 40020021364
• NII Book ID: AA1105098X
• DOI: 10.14490/jjss.43.203
• ISSN: 13486365
• ISSN: 18822754
• NDL BIB ID: 025352540
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I025352540
• Web Site: https://www.jstage.jst.go.jp/article/jjss/43/2/43_203/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed