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Estimating discrete Markov models from various incomplete data schemes

  • Pasanisi, Alberto
  • Fu, Shuai
  • Bousquet, Nicolas
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    The parameters of a discrete stationary Markov model are transition probabilities between states. Traditionally, data consist in sequences of observed states for a given number of individuals over the whole observation period. In such a case, the estimation of transition probabilities is straightforwardly made by counting one-step moves from a given state to another. In many real-life problems, however, the inference is much more difficult as state sequences are not fully observed, namely the state of each individual is known only for some given values of the time variable. A review of the problem is given, focusing on Monte Carlo Markov Chain (MCMC) algorithms to perform Bayesian inference and evaluate posterior distributions of the transition probabilities in this missing-data framework. Leaning on the dependence between the rows of the transition matrix, an adaptive MCMC mechanism accelerating the classical Metropolis–Hastings algorithm is then proposed and empirically studied.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312001090
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    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 56 (2012)
    Issue (Month): 9 ()
    Pages: 2609-2625

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    Handle: RePEc:eee:csdana:v:56:y:2012:i:9:p:2609-2625
    DOI: 10.1016/j.csda.2012.02.027
    Contact details of provider: Web page: http://www.elsevier.com/locate/csda

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    1. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "On sovereign credit migration: A study of alternative estimators and rating dynamics," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3448-3469, April.
    2. Gouno, E. & Courtrai, L. & Fredette, M., 2011. "Estimation from aggregate data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 615-626, January.
    3. David J. Nott & Robert Kohn, 2005. "Adaptive sampling for Bayesian variable selection," Biometrika, Biometrika Trust, vol. 92(4), pages 747-763, December.
    4. repec:dau:papers:123456789/1906 is not listed on IDEAS
    5. Isabelle Deltour & Sylvia Richardson & Jean-Yves Le Hesran, 1999. "Stochastic Algorithms for Markov Models Estimation with Intermittent Missing Data," Biometrics, The International Biometric Society, vol. 55(2), pages 565-573, 06.
    6. Huard, David & Evin, Guillaume & Favre, Anne-Catherine, 2006. "Bayesian copula selection," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 809-822, November.
    7. Matthew T Jones, 2005. "Estimating Markov Transition Matrices Using Proportions Data; An Application to Credit Risk," IMF Working Papers 05/219, International Monetary Fund.
    8. MacRae, Elizabeth Chase, 1977. "Estimation of Time-Varying Markov Processes with Aggregate Data," Econometrica, Econometric Society, vol. 45(1), pages 183-98, January.
    9. Christian Genest & Jean-François Quessy & Bruno Rémillard, 2006. "Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 337-366.
    10. Nikoloulopoulos, Aristidis K. & Karlis, Dimitris, 2008. "Copula model evaluation based on parametric bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3342-3353, March.
    11. Vihola, Matti, 2010. "Grapham: Graphical models with adaptive random walk Metropolis algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 49-54, January.
    12. Rosenthal, Jeffrey S., 2007. "AMCMC: An R interface for adaptive MCMC," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5467-5470, August.
    13. Jerome A. Dupuis & Carl James Schwarz, 2007. "A Bayesian Approach to the Multistate Jolly–Seber Capture–Recapture Model," Biometrics, The International Biometric Society, vol. 63(4), pages 1015-1022, December.
    14. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
    15. Strid, Ingvar & Giordani, Paolo & Kohn, Robert, 2010. "Adaptive hybrid Metropolis-Hastings samplers for DSGE models," SSE/EFI Working Paper Series in Economics and Finance 724, Stockholm School of Economics.
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