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
fDate :
3/1/2012 12:00:00 AM
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;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.2011.2182399