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International Conference on Analytical and Computational Methods in Probability Theory

ACMPT 2017: Analytical and Computational Methods in Probability Theory pp 485–496Cite as

Statistical Analysis of Big Data Based on Parsimonious Models of High-Order Markov Chains

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10684))

Abstract

The paper is devoted to construction of parsimonious (small-parametric) models of high-order Markov chains and to computer algorithms for statistical inferences on parameters of these models.

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References

  1. Kedem, B., Fokianos, K.: Regression Models for Time Series. John Wiley, New York (2002)

    Book  MATH  Google Scholar 

  2. Buhlmann, P., Wyner, A.J.: Variable length Markov chains. Ann. Stat. 27(2), 480–513 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  3. Kharin, Y.S.: Robustness in Statistical Forecasting. Springer, New York (2013)

    Book  MATH  Google Scholar 

  4. Kharin, Y.S., Piatlitski, A.I.: A Markov chain of order \(s\) with \(r\) partial connections and statistical inference on its parameters. Discret. Math. Appl. 17(3), 295–317 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  5. Kharin, Y., Maltsew, M.: Markov chain of conditional order: properties and statistical analysis. Austrian J. Stat. 43(3–4), 205–217 (2014)

    Article  Google Scholar 

  6. Jacobs, P.A., Lewis, P.A.W.: Discrete time series generated by mixtures I: correlational and runs properties. J. Roy. Stat. Soc. Ser. B. 40(1), 94–105 (1978)

    MathSciNet  MATH  Google Scholar 

  7. Raftery, A.: A model for high-order Markov chains. J. Roy. Stat. Soc. Ser. B. 47(3), 528–539 (1985)

    MathSciNet  MATH  Google Scholar 

  8. Voloshko, V., Kharin, Y.: On statistical estimation of parameters for a family of binary autoregressive time series. In: Abstracts of the European Meeting of Statisticians, pp. 146–147. Helsinki (2017)

    Google Scholar 

  9. Fan, J., Yao, Q.: Nonlinear Time Series: Nonparametric and Parametric Methods. Springer, New York (2003)

    Book  MATH  Google Scholar 

  10. Raftery, A., Tavare, S.: Estimation and modelling repeated patterns in high order Markov chains with the MTD model. Appl. Stat. 43, 179–199 (1994)

    Article  MATH  Google Scholar 

  11. Kharin, A., Kishylau, D.: Robust sequential test for hypotheses about discrete distributions in the presence of “outliers”. J. Math. Sci. 205(1), 68–73 (2015)

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Research Institute for Applied Problems of Mathematics and Informatics, Belarusian State University, 220030, Minsk, Belarus

    Yu. S. Kharin

Authors
  1. Yu. S. Kharin
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Corresponding author

Correspondence to Yu. S. Kharin .

Editor information

Editors and Affiliations

  1. Department of Applied Probability and Informatics, RUDN University, Moscow, Russia

    Vladimir V. Rykov

  2. City University of Hong Kong, Hong Kong, Hong Kong

    Nozer D. Singpurwalla

  3. Steklov Mathematical Institute of Russian Academy of Sciences, Moscow, Russia

    Andrey M. Zubkov

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Kharin, Y.S. (2017). Statistical Analysis of Big Data Based on Parsimonious Models of High-Order Markov Chains. In: Rykov, V., Singpurwalla, N., Zubkov, A. (eds) Analytical and Computational Methods in Probability Theory. ACMPT 2017. Lecture Notes in Computer Science(), vol 10684. Springer, Cham. https://doi.org/10.1007/978-3-319-71504-9_40

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  • DOI: https://doi.org/10.1007/978-3-319-71504-9_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71503-2

  • Online ISBN: 978-3-319-71504-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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