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Markov Chains: Models, Algorithms and Applications

Author

Listed:
  • Wai-Ki Ching

    (The University of Hong Kong)

  • Michael K. Ng

    (Hong Kong Baptist University)

Abstract

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Suggested Citation

  • Wai-Ki Ching & Michael K. Ng, 2006. "Markov Chains: Models, Algorithms and Applications," International Series in Operations Research and Management Science, Springer, number 978-0-387-29337-0, March.
    • Handle: RePEc:spr:isorms:978-0-387-29337-0
    DOI: 10.1007/0-387-29337-X
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    Citations

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    Cited by:

    1. Joseph Gogodze, 2021. "Ranking Demographic Conditions: MCDM Approach," SN Operations Research Forum, Springer, vol. 2(2), pages 1-12, June.
    2. Edward Sandoyan & David Manukyan, 2013. "Exchange Rate Forecast: a New Approach for Armenian Dram," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 20(2), pages 159-177, October.
    3. João Nicolau & Flavio Riedlinger, 2015. "Estimation and inference in multivariate Markov chains," Statistical Papers, Springer, vol. 56(4), pages 1163-1173, November.
    4. D’Amico, Guglielmo & De Blasis, Riccardo & Petroni, Filippo, 2023. "The Mixture Transition Distribution approach to networks: Evidence from stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    5. Alicja Ganczarek-Gamrot & Józef Stawicki, 2017. "Comparison of certain dynamic estimation methods of Value at Risk on Polish gas market," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 81-96.
    6. Suryadeepto Nag & Sankarshan Basu & Siddhartha P. Chakrabarty, 2022. "Modeling the Commodity Prices of Base Metals in Indian Commodity Market Using a Higher Order Markovian Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 159-171, March.
    7. Perkin, Joshuah S. & Gido, Keith B. & Al-Ta’ani, Ola & Scoglio, Caterina, 2013. "Simulating fish dispersal in stream networks fragmented by multiple road crossings," Ecological Modelling, Elsevier, vol. 257(C), pages 44-56.
    8. Otero, Dino & Galetti, Diógenes & Mizrahi, Salomon S., 2018. "Modeling vehicular traffic networks. Part I," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 97-110.
    9. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    10. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.
    11. Bruno Damásio & João Nicolau, 2020. "Time Inhomogeneous Multivariate Markov Chains: Detecting and Testing Multiple Structural Breaks Occurring at Unknown," Working Papers REM 2020/0136, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    12. Babak Omidvar & Mohammad Hojjati Malekshah & Hamed Omidvar, 2014. "Failure risk assessment of interdependent infrastructures against earthquake, a Petri net approach: case study—power and water distribution networks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(3), pages 1971-1993, April.
    13. Villacorta, Pablo J. & Verdegay, José L., 2016. "FuzzyStatProb: An R Package for the Estimation of Fuzzy Stationary Probabilities from a Sequence of Observations of an Unknown Markov Chain," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 71(i08).
    14. Peter Sendfeld, 2008. "Two Queues with Weighted One-Way Overflow," Methodology and Computing in Applied Probability, Springer, vol. 10(4), pages 531-555, December.
    15. Józef Stawicki, 2016. "Using the First Passage Times in Markov Chain model to support financial decisions on the stock exchange," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 37-47.
    16. Jokar, Meysam & Salarieh, Hassan & Alasty, Aria, 2019. "On the existence of proper stochastic Markov models for statistical reconstruction and prediction of chaotic time series," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 373-382.
    17. Michael K. Ng & Yuho Chung, 2012. "Double Mover–Stayer model on customer switching in telecommunications industry," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(8), pages 663-674, December.
    18. Dong-Mei Zhu & Wai-Ki Ching & Robert J. Elliott & Tak-Kuen Siu & Lianmin Zhang, 2017. "A Higher-order interactive hidden Markov model and its applications," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1055-1069, October.

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