Hierarchical subspace models for contingency tables

Hisayuki Hara, Tomonari Sei, A. Takemura Akimichi

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


For the statistical analysis of multiway contingency tables, we propose modeling interaction terms in each maximal compact component of a hierarchical model. By this approach we can search for parsimonious models with smaller degrees of freedom than the usual hierarchical model, while preserving the localization property of the inference in the hierarchical model. This approach also enables us to evaluate the localization property of a given log-affine model. We discuss estimation and exact tests of the proposed model and illustrate the advantage of the proposed modeling with some data sets.

Original languageEnglish
Pages (from-to)19-34
Number of pages16
JournalJournal of Multivariate Analysis
Issue number1
Publication statusPublished - 2012 Jan


  • 62H05
  • 62H17
  • Context specific interaction model
  • Divider
  • Markov bases
  • Split model
  • Uniform association model

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty


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