Detection of Blocks in a Binary Matrix — A Bayesian Approach

  • W. Vach
  • K. W. Alt
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


A binary matrix representing the presence of traits and objects is given. We consider the task to detect a subblock of traits and objects such that for each trait its frequency of occurrence within these objects is highly increased. A Bayesian framework is specified and the Gibbs sampler is used to approximate the posterior distribution. The necessary extensions to use this procedure for kinship analysis in prehistoric anthropology are outlined.


Posterior Distribution Prior Distribution Bayesian Framework Binary Matrix Kinship Analysis 
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Copyright information

© Springer-Verlag Berlin · Heidelberg 1996

Authors and Affiliations

  • W. Vach
    • 1
  • K. W. Alt
    • 2
  1. 1.Institute of Medical Biometry and Medical InformaticsUniversity of FreiburgFreiburgGermany
  2. 2.Institute of Forensic MedicineDüsseldorf UniversityDüsseldorfGermany

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