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Tests for Multiple Change Points in Binary Markov Sequences

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From Data and Information Analysis to Knowledge Engineering

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Abstract

In Krauth (2005) we derived a finite conditional conservative test for a change point in a Bernoulli sequence with first-order Markov dependence. This approach was based on the property of intercalary independence of Markov processes (Dufour and Torrès (2000)) and on the CUSUM statistic considered in Krauth (1999, 2000) for the case of independent binomial trials. Here, we derive finite conditional tests for multiple change points in binary first-order Markov sequences using in addition conditional modified maximum likelihood estimates for multiple change points (Krauth, 2004) and Exact Fisher tests.

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Author information

Authors and Affiliations

  1. Institute of Experimental Psychology, University of Düsseldorf, D-40225, Düsseldorf, Germany

    Joachim Krauth

Authors
  1. Joachim Krauth
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Editor information

Editors and Affiliations

  1. Institut für Technische und Betriebliche Informationssysteme, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Myra Spiliopoulou

  2. Institut für Wissens- und Sprachverarbeitung, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Rudolf Kruse , Christian Borgelt  & Andreas Nürnberger ,  & 

  3. Institut für Entscheidungstheorie und Unternehmensforschung, Universität Karlsruhe (TH), 76128, Karlsruhe

    Wolfgang Gaul

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© 2006 Springer Berlin · Heidelberg

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Krauth, J. (2006). Tests for Multiple Change Points in Binary Markov Sequences. In: Spiliopoulou, M., Kruse, R., Borgelt, C., Nürnberger, A., Gaul, W. (eds) From Data and Information Analysis to Knowledge Engineering. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31314-1_82

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