IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v182y2022ics0167715221002637.html
   My bibliography  Save this article

A decoupling principle for Markov-modulated chains

Author

Listed:
  • Qiu, Qinjing
  • Kawai, Reiichiro

Abstract

Markov modulation has been widely employed in various fields of application, such as finance, economics, information and computer sciences, operations research, healthcare, and bio-medicines, whereas the additional modeling flexibility comes at the cost of demanding computation and complex inference procedure. The aim of this paper is to establish a decoupling principle for Markov-modulated chains, which enables one to represent an expectation on a Markov-modulated chain by a convergent sequence written on a set of ordinary continuous-time Markov chains. The proposed decoupling principle covers a large class of Markov-modulated chains, ranging from a variety of Markov-modulated processes to time-inhomogeneous models without time-discretization of the generator matrices, and has great potential for easing the computation around Markov-modulated chains.

Suggested Citation

  • Qiu, Qinjing & Kawai, Reiichiro, 2022. "A decoupling principle for Markov-modulated chains," Statistics & Probability Letters, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:stapro:v:182:y:2022:i:c:s0167715221002637
    DOI: 10.1016/j.spl.2021.109301
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715221002637
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2021.109301?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. U. Yechiali & P. Naor, 1971. "Queuing Problems with Heterogeneous Arrivals and Service," Operations Research, INFORMS, vol. 19(3), pages 722-734, June.
    2. Jackson, Christopher, 2011. "Multi-State Models for Panel Data: The msm Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 38(i08).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qinjing Qiu & Reiichiro Kawai, 2023. "Iterative Weak Approximation and Hard Bounds for Switching Diffusion," Journal of Theoretical Probability, Springer, vol. 36(2), pages 1003-1036, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vernon T. Farewell & Li Su & Christopher Jackson, 2019. "Partially hidden multi-state modelling of a prolonged disease state defined by a composite outcome," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 696-711, October.
    2. Gaffney, Edward & McCann, Fergal, 2019. "The cyclicality in SICR: mortgage modelling under IFRS 9," ESRB Working Paper Series 92, European Systemic Risk Board.
    3. Biagini, Francesca & Groll, Andreas & Widenmann, Jan, 2013. "Intensity-based premium evaluation for unemployment insurance products," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 302-316.
    4. Sharples, Linda D., 2018. "The role of statistics in the era of big data: Electronic health records for healthcare research," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 105-110.
    5. Alex Bottle & Chiara Maria Ventura & Kumar Dharmarajan & Paul Aylin & Francesca Ieva & Anna Maria Paganoni, 2018. "Regional variation in hospitalisation and mortality in heart failure: comparison of England and Lombardy using multistate modelling," Health Care Management Science, Springer, vol. 21(2), pages 292-304, June.
    6. Jianjun Li & Liwei Liu & Tao Jiang, 2018. "Analysis of an M/G/1 queue with vacations and multiple phases of operation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(1), pages 51-72, February.
    7. Wildhaber, Mark L. & Albers, Janice L. & Green, Nicholas S. & Moran, Edward H., 2017. "A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example," Ecological Modelling, Elsevier, vol. 359(C), pages 434-448.
    8. Budhi Surya, 2021. "A new class of conditional Markov jump processes with regime switching and path dependence: properties and maximum likelihood estimation," Papers 2107.07026, arXiv.org.
    9. Tsiropoulos, Vasilis, 2018. "A Vulnerability Analysis for Mortgaged Irish Households," Financial Stability Notes 02-18, Central Bank of Ireland.
    10. João Costa Freitas & Alberto Adrego Pinto & Óscar Felgueiras, 2024. "Game Theory for Predicting Stocks’ Closing Prices," Mathematics, MDPI, vol. 12(17), pages 1-49, August.
    11. Sarrias, Mauricio, 2021. "A two recursive equation model to correct for endogeneity in latent class binary probit models," Journal of choice modelling, Elsevier, vol. 40(C).
    12. Emanuel Krebs & Jeong E. Min & Elizabeth Evans & Libo Li & Lei Liu & David Huang & Darren Urada & Thomas Kerr & Yih-Ing Hser & Bohdan Nosyk, 2017. "Estimating State Transitions for Opioid Use Disorders," Medical Decision Making, , vol. 37(5), pages 483-497, July.
    13. Guglielmo D'Amico & Stefania Scocchera & Loriano Storchi, 2021. "Randentropy: a software to measure inequality in random systems," Papers 2103.09107, arXiv.org.
    14. Wood, Kevin A. & Hilton, Geoff M. & Newth, Julia L. & Rees, Eileen C., 2019. "Seasonal variation in energy gain explains patterns of resource use by avian herbivores in an agricultural landscape: Insights from a mechanistic model," Ecological Modelling, Elsevier, vol. 409(C), pages 1-1.
    15. Sy-Miin Chow & Guangjian Zhang, 2013. "Nonlinear Regime-Switching State-Space (RSSS) Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 740-768, October.
    16. Cristian Preda & Quentin Grimonprez & Vincent Vandewalle, 2021. "Categorical Functional Data Analysis. The cfda R Package," Mathematics, MDPI, vol. 9(23), pages 1-31, November.
    17. Michael Crowther & Paul Lambert, 2016. "Multistate survival analysis in Stata," United Kingdom Stata Users' Group Meetings 2016 02, Stata Users Group.
    18. Pauhofová, Iveta & Želinský, Tomáš, 2017. "On the Regional Convergence of Income at District Level in Slovakia," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 65(10), pages 918-934.
    19. Spitoni Cristian & Verduijn Marion & Putter Hein, 2012. "Estimation and Asymptotic Theory for Transition Probabilities in Markov Renewal Multi-State Models," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-39, August.
    20. Jain, Manisha & Rao, Anand B. & Patwardhan, Anand, 2018. "Appliance labeling and consumer heterogeneity: A discrete choice experiment in India," Applied Energy, Elsevier, vol. 226(C), pages 213-224.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:182:y:2022:i:c:s0167715221002637. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.