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Robustness in Sequential Discrimination of Markov Chains under “Contamination”

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Theory and Applications of Recent Robust Methods

Part of the book series: Statistics for Industry and Technology ((SIT))

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Abstract

The problem of robustness is considered for sequential hypotheses testing on the parameters of Markov chains. The exact expressions for the conditional error probabilities, and for the conditional expected sequence lengths are obtained. Robustness analysis under “contamination” is performed. Numerical results are given to illustrate the theory.

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References

  1. R. Durbin, S. Eddy, A. Krogh, and G. Mitchison, Biological Sequence Analysis. Cambridge University Press, 1998.

    Google Scholar 

  2. F. Hampel, E. Ronchetti, P. Rousseeuw, and W. Stahel, Robust Statistics. The Approach Based on Influence Functions. Wiley, New York, 1986.

    MATH  Google Scholar 

  3. P. Huber, Robust Statistics. Wiley, New York, 1981.

    Book  MATH  Google Scholar 

  4. A. Kharin, On Robustifying of the SPRT For a Discrete Model Under “Contaminations”. Austrian J. Statist. 31 (2002), 267–277.

    Google Scholar 

  5. J. G. Kemeni and J. L. Snell, Finite Markov chains. Wiley, New York, 1959.

    Google Scholar 

  6. M. Malyutov and I. Tsitovich, Asymptotically Optimal Sequential Testing of Hypotheses. Problems Inform. Transmission 36 (2000), 98–112.

    MathSciNet  Google Scholar 

  7. D. Siegmund, Sequential Analysis. Tests and Confidence Intervals. Springer, New York, 1985.

    MATH  Google Scholar 

  8. N. Stockinger and R. Dutter, Robust Time Series Analysis: a Survey. Kybernetika 23 (1987), 1–90.

    MathSciNet  Google Scholar 

  9. A. Wald, Sequential Analysis. Wiley, New York, 1947.

    MATH  Google Scholar 

  10. J. Whitehead, The Design and Analysis of Sequential Clinical Trials. Wiley, New York, 1997.

    Google Scholar 

  11. T.-J. Wu, Ya-Ch. Hsieh, and L.-A. Li, Statistical Measures of DNA Sequence Dissimilarity Under Markov Chain Models of Base Composition. Biometrics 57 (2001), 441–448.

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Belarussian State University, Fr. Skoriny av., 4, BY 220050, Minsk, Belarus

    A. Kharin

Authors
  1. A. Kharin
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Editor information

Editors and Affiliations

  1. Department of Mathematics, Katholieke Universiteit Leuven, W. de Croylaan 54, 3001, Leuven, Belgium

    Mia Hubert

  2. Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 S9, 9000, Gent, Belgium

    Greet Pison  & Stefan Van Aelst  & 

  3. Department of Mathematics and Computer Science, University of Antwerp, Middelheimlaan 1, 2020, Antwerp, Belgium

    Anja Struyf

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© 2004 Springer Basel AG

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Kharin, A. (2004). Robustness in Sequential Discrimination of Markov Chains under “Contamination”. In: Hubert, M., Pison, G., Struyf, A., Van Aelst, S. (eds) Theory and Applications of Recent Robust Methods. Statistics for Industry and Technology. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-7958-3_15

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  • DOI: https://doi.org/10.1007/978-3-0348-7958-3_15

  • Publisher Name: Birkhäuser, Basel

  • Print ISBN: 978-3-0348-9636-8

  • Online ISBN: 978-3-0348-7958-3

  • eBook Packages: Springer Book Archive

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