IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2007i9p4254-4268.html
   My bibliography  Save this article

Predictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approach

Author

Listed:
  • Yu, Jun-Wu
  • Tian, Guo-Liang
  • Tang, Man-Lai

Abstract

No abstract is available for this item.

Suggested Citation

  • Yu, Jun-Wu & Tian, Guo-Liang & Tang, Man-Lai, 2007. "Predictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4254-4268, May.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:9:p:4254-4268
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(06)00157-5
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Shaul Bar-Lev & Idit Lavi & Benjamin Reiser, 1992. "Bayesian inference for the power law process," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 44(4), pages 623-639, December.
    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. Yongquan, Sun & Xi, Chen & He, Ren & Yingchao, Jin & Quanwu, Liu, 2016. "Ordering decision-making methods on spare parts for a new aircraft fleet based on a two-sample prediction," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 40-50.
    2. Tarakci, Hakan & Tang, Kwei & Teyarachakul, Sunantha, 2009. "Learning effects on maintenance outsourcing," European Journal of Operational Research, Elsevier, vol. 192(1), pages 138-150, January.
    3. Hermann, Simone & Ickstadt, Katja & Müller, Christine H., 2018. "Bayesian prediction for a jump diffusion process – With application to crack growth in fatigue experiments," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 83-96.
    4. Gilardoni, Gustavo L. & Oliveira, Maristela D. de & Colosimo, Enrico A., 2013. "Nonparametric estimation and bootstrap confidence intervals for the optimal maintenance time of a repairable system," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 113-124.

    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. Almeida, Marco Pollo & Paixão, Rafael S. & Ramos, Pedro L. & Tomazella, Vera & Louzada, Francisco & Ehlers, Ricardo S., 2020. "Bayesian non-parametric frailty model for dependent competing risks in a repairable systems framework," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    2. Alicja Jokiel-Rokita & Ryszard Magiera, 2023. "Bayesian estimation versus maximum likelihood estimation in the Weibull-power law process," Computational Statistics, Springer, vol. 38(2), pages 675-710, June.
    3. Yu, Jun-Wu & Tian, Guo-Liang & Tang, Man-Lai, 2008. "Statistical inference and prediction for the Weibull process with incomplete observations," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1587-1603, January.
    4. Rama Lingham & S. Sivaganesan, 1997. "Testing Hypotheses About the Power Law Process Under Failure Truncation Using Intrinsic Bayes Factors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(4), pages 693-710, December.
    5. Fabrizio Ruggeri & Siva Sivaganesan, 2005. "On Modeling Change Points in Non-Homogeneous Poisson Processes," Statistical Inference for Stochastic Processes, Springer, vol. 8(3), pages 311-329, December.

    More about this item

    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:eee:csdana:v:51:y:2007:i:9:p:4254-4268. 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/locate/csda .

    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.