• DocumentCode
    1437016
  • Title

    An Approximate Solution to the G–Renewal Equation With an Underlying Weibull Distribution

  • Author

    Yevkin, Olexandr ; Krivtsov, Vasiliy

  • Author_Institution
    Dyaden Int. Ltd., Toronto, ON, Canada
  • Volume
    61
  • Issue
    1
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    68
  • Lastpage
    73
  • Abstract
    An important characteristic of the g-renewal process, of great practical interest, is the g-renewal equation, which represents the expected cumulative number of recurrent events as a function of time. Just like in an ordinary renewal process, the problem is that the g-renewal equation does not have a closed form solution, unless the underlying event times are exponentially distributed. The Monte Carlo solution, although exhaustive, is computationally demanding. This paper offers a simple-to-implement (in an Excel spreadsheet) approximate solution, when the underlying failure-time distribution is Weibull. The accuracy of the proposed solution is in the neighborhood of 2%, when compared to the respective Monte Carlo solution. Based on the proposed solution, we also consider an estimation procedure of the g-renewal process parameters.
  • Keywords
    Monte Carlo methods; Weibull distribution; Monte Carlo solution; Weibull distribution; g-renewal equation; Accuracy; Approximation methods; Equations; Estimation; Mathematical model; Monte Carlo methods; Shape; Cumulative intensity function; G–renewal process; Weibull distribution;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/TR.2011.2182399
  • Filename
    6144045