A conditional Monte Carlo with intermediate estimations for computing MTTF of Markovian systems

نویسندگان

  • Leslie Murray
  • Hector Cancela
  • Gerardo Rubino
چکیده

Conditional Monte Carlo with intermediate estimations is a proposal for applying Conditional Monte Carlo to the estimation of the failure probability of a multicomponent system modeled by a Markov chain. Through this probability it is possible to compute the MTTF. This article introduces the basis of this method, proves that it is unbiased, that its variance is less than the standard simulation and mentions some lines of ongoing work for extending the idea and applying it to systems with large number of states.

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تاریخ انتشار 2013