IDEAS home Printed from https://ideas.repec.org/a/spr/metcap/v12y2010i2d10.1007_s11009-009-9138-2.html
   My bibliography  Save this article

A Non-Homogeneous Continuous Time Semi-Markov Model for the Study of Accumulated Claim Process

Author

Listed:
  • Giuseppe Di Biase

    (Università “G. D’Annunzio”)

  • Jacques Janssen

    (Université de Bretagne Occidentale)

  • Raimondo Manca

    (Università di Roma “La Sapienza”)

Abstract

The accumulated claim process is the summed total of all claims starting from time t. The semi-Markov environment, at authors’ opinion, is able to follow the evolution of this process. In the paper a continuous time non-homogeneous semi-Markov model with a denumerable set of states will be used to follow the stochastic evolution of the accumulated claim process.

Suggested Citation

  • Giuseppe Di Biase & Jacques Janssen & Raimondo Manca, 2010. "A Non-Homogeneous Continuous Time Semi-Markov Model for the Study of Accumulated Claim Process," Methodology and Computing in Applied Probability, Springer, vol. 12(2), pages 227-235, June.
    • Handle: RePEc:spr:metcap:v:12:y:2010:i:2:d:10.1007_s11009-009-9138-2
    DOI: 10.1007/s11009-009-9138-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11009-009-9138-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11009-009-9138-2?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. Janssen, Jacques & Reinhard, Jean-Marie, 1985. "Probabilités de Ruine pour une Classe de Modèles de Risque Semi-Markoviens," ASTIN Bulletin, Cambridge University Press, vol. 15(2), pages 123-133, November.
    2. Sophie Mercier, 2008. "Numerical Bounds for Semi-Markovian Quantities and Application to Reliability," Methodology and Computing in Applied Probability, Springer, vol. 10(2), pages 179-198, June.
    Full references (including those not matched with items on IDEAS)

    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. O. J. Boxma & M. R. H. Mandjes, 2022. "Queueing and risk models with dependencies," Queueing Systems: Theory and Applications, Springer, vol. 102(1), pages 69-86, October.
    2. Schmidli, Hanspeter, 2001. "Distribution of the first ladder height of a stationary risk process perturbed by [alpha]-stable Lévy motion," Insurance: Mathematics and Economics, Elsevier, vol. 28(1), pages 13-20, February.
    3. Siegl, Thomas & Tichy, Robert F., 1999. "A process with stochastic claim frequency and a linear dividend barrier," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 51-65, March.
    4. Cossette, Helene & Landriault, David & Marceau, Etienne, 2004. "Compound binomial risk model in a markovian environment," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 425-443, October.
    5. Albrecher, Hansjorg & Boxma, Onno J., 2005. "On the discounted penalty function in a Markov-dependent risk model," Insurance: Mathematics and Economics, Elsevier, vol. 37(3), pages 650-672, December.
    6. Guglielmo D’Amico & Fulvio Gismondi & Jacques Janssen & Raimondo Manca, 2015. "Discrete Time Homogeneous Markov Processes for the Study of the Basic Risk Processes," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 983-998, December.
    7. Yunhui Hou & Nikolaos Limnios & Walter Schön, 2017. "On the Existence and Uniqueness of Solution of MRE and Applications," Methodology and Computing in Applied Probability, Springer, vol. 19(4), pages 1241-1250, December.
    8. Zhou, Zhongbao & Xiao, Helu & Deng, Yingchun, 2015. "Markov-dependent risk model with multi-layer dividend strategy," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 273-286.
    9. Chen, Mi & Yuen, Kam Chuen & Guo, Junyi, 2014. "Survival probabilities in a discrete semi-Markov risk model," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 205-215.
    10. Inma T Castro & Sophie Mercier, 2016. "Performance measures for a deteriorating system subject to imperfect maintenance and delayed repairs," Journal of Risk and Reliability, , vol. 230(4), pages 364-377, August.

    More about this item

    Keywords

    Semi-Markov; Reward; Risk theory;
    All these keywords.

    Statistics

    Access and download statistics

    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:spr:metcap:v:12:y:2010:i:2:d:10.1007_s11009-009-9138-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.