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Recursive moment formulas for regenerative simulation

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Abstract

Let f be a real-valued function defined on the state space of a regenerative process \( \mathop X\limits_ \eqsim = \left\{ {X\left( t \right):t \geqslant 0} \right\}\) with regeneration times 0 = T0 < T1 <..., and suppose that

$$ {r_t} = \frac{1}{t}\int_0^t {f\left( {X\left( s \right)} \right)ds \to r\quad a.s.} $$
(1.1)

as t → ∞.

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References

  • M.A. Crane, D.L. Iglehart (1975). “Stimulating Stable Stochastic Systems, III: Regenerative Processes and Discrete-Event Stimulations”, Oper. Res. 23, 33–45.

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  • P.W. Glynn (1982), “Asymptotic Theory for Nonparametric Confidence Intervals”, Technical Report no 19 Dept. of Operations Research, Stanford University, Stanford, CA.

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  • P.W. Glynn and D.L. Iglehart (1984), “The Joint Limit Distribution of Sample Mean and the Regenerative Variance Estimator”. Forthcoming technical report, Dept. of Operations Research, Stanford University, Stanford, CA.

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  • A. Hordijk, D.L. Iglehart and R. Schassberger (1976). “Discrete-Time Methods of Stimulating Continuous-Time Markov Chains”, Advances in Appl. Probability 8, 772–788.

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© 1986 Springer Science+Business Media New York

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Glynn, P.W., Iglehart, D.L. (1986). Recursive moment formulas for regenerative simulation. In: Janssen, J. (eds) Semi-Markov Models. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-0574-1_7

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  • DOI: https://doi.org/10.1007/978-1-4899-0574-1_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4899-0576-5

  • Online ISBN: 978-1-4899-0574-1

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