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Fitting Markov chain models to discrete state series such as DNA sequences

Author

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  • P. J. Avery
  • D. A. Henderson

Abstract

Discrete state series such as DNA sequences can often be modelled by Markov chains. The analysis of such series is discussed in the context of log‐linear models. The data produce contingency tables with similar margins due to the dependence of the observations. However, despite the unusual structure of the tables, the analysis is equivalent to that for data from multinomial sampling. The reason why the standard number of degrees of freedom is correct is explained by using theoretical arguments and the asymptotic distribution of the deviance is verified empirically. Problems involved with fitting high order Markov chain models, such as reduced power and computational expense, are also discussed.

Suggested Citation

  • P. J. Avery & D. A. Henderson, 1999. "Fitting Markov chain models to discrete state series such as DNA sequences," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(1), pages 53-61.
  • Handle: RePEc:bla:jorssc:v:48:y:1999:i:1:p:53-61
    DOI: 10.1111/1467-9876.00139
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    1. repec:aaa:journl:v:3:y:1999:i:1:p:87-100 is not listed on IDEAS
    2. Jonsson, Robert, 2011. "A Markov Chain Model for Analysing the Progression of Patient’s Health States," Research Reports 2011:6, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    3. Gabadinho, Alexis & Ritschard, Gilbert, 2016. "Analyzing State Sequences with Probabilistic Suffix Trees: The PST R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i03).
    4. J. Besag & D. Mondal, 2013. "Exact Goodness-of-Fit Tests for Markov Chains," Biometrics, The International Biometric Society, vol. 69(2), pages 488-496, June.
    5. M. L. Menéndez & L. Pardo & M. C. Pardo & K. Zografos, 2011. "Testing the Order of Markov Dependence in DNA Sequences," Methodology and Computing in Applied Probability, Springer, vol. 13(1), pages 59-74, March.
    6. Jonsson, Robert, 2011. "Tests of Markov Order and Homogeneity in a Markov Chain," Research Reports 2011:7, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    7. Anastasios N. Arapis & Frosso S. Makri & Zaharias M. Psillakis, 2017. "Joint distribution of k-tuple statistics in zero-one sequences of Markov-dependent trials," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-13, December.
    8. Varin, Cristiano & Vidoni, Paolo, 2006. "Pairwise likelihood inference for ordinal categorical time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2365-2373, December.

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