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Geometric-Moment Contraction of G/G/1 Waiting Times

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Abstract

For asymptotically valid point and confidence-interval (CI) estimation of steady-state quantiles in dependent simulation output processes, two recent output-analysis procedures assume that those processes satisfy the geometric-moment contraction (GMC) condition. Moreover, the GMC condition ensures satisfaction of most of the other assumptions underlying those procedures, which are based on the techniques of batch means and standardized time series, respectively. For performance evaluation of the associated point and CI estimators, the G/G/1 queueing system provides gold-standard test processes. We prove that the GMC condition holds for G/G/1 queue-waiting times obtained with a non-heavy-tailed service-time distribution (i.e., its moment generating function exists in a neighborhood of zero). This result complements earlier proofs that the GMC condition holds for many widely used time-series and Markov-chain processes. A robustness study illustrates empirical verification of the GMC condition for M/G/1 queue-waiting times obtained with non-heavy-tailed and heavy-tailed service-time distributions.

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References

  1. Aktaran-Kalaycı, T., Alexopoulos, C., Argon, N.T., Goldsman, D., Wilson, J.R.: Exact expected values of variance estimators in steady-state simulation. Nav. Res. Logist. 54(4), 397–410 (2007)

    Article  MATH  Google Scholar 

  2. Alexopoulos, C., Argon, N.T., Goldsman, D., Tokol, G., Wilson, J.R.: Overlapping variance estimators for simulation. Oper. Res. 55(6), 1090–1103 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  3. Alexopoulos, C., Boone, J.H., Goldsman, D., Lolos, A., Dingeç, K.D., Wilson, J.R.: Steady-state quantile estimation using standardized time series. In: K.H. Bae, B. Feng, S. Kim, L. Lazarova-Molnar, Z. Zheng, T. Roeder, R. Thiesing (eds.) Proceedings of the 2020 Winter Simulation Conference, pp. 289–300. Institute of Electrical and Electronics Engineers, Piscataway, New Jersey (2020)

    Google Scholar 

  4. Alexopoulos, C., Dingeç, K.D., Goldsman, D., Lolos, A., Mokashi, A.C., Wilson, J.R.: Steady-state quantile estimation using standardized time series. Technical report (2022). https://people.engr.ncsu.edu/jwilson/files/stsms-112821.pdf. Accessed 10th Feb 2022

  5. Alexopoulos, C., Goldsman, D., Mokashi, A.C., Tien, K.W., Wilson, J.R.: Sequest: a sequential procedure for estimating quantiles in steady-state simulations. Oper. Res. 67(4), 1162–1183 (2019). https://people.engr.ncsu.edu/jwilson/files/sequest19or.pdf. Accessed 7th Sept 2019

  6. Alexopoulos, C., Goldsman, D., Wilson, J.R.: A new perspective on batched quantile estimation. In: C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, A.M. Uhrmacher (eds.) Proceedings of the 2012 Winter Simulation Conference, pp. 190–200. Institute of Electrical and Electronics Engineers, Piscataway, New Jersey (2012)

    Google Scholar 

  7. Asmussen, S., Glynn, P.W.: Stochastic Simulation: Algorithms and Analysis. Springer, New York (2007)

    Book  MATH  Google Scholar 

  8. Beran, J.: Statistics for Long-Memory Processes. Chapman & Hall/CRC, Boca Raton, Florida (1994)

    MATH  Google Scholar 

  9. Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. J. Econ. 31, 307–327 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  10. Damerdji, H.: Strong consistency of the variance estimator in steady-state simulation output analysis. Math. Oper. Res. 19, 494–512 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  11. Davis, P.J., Rabinowitz, P.: Methods of Numerical Integration, 2nd edn. Academic Press, Orlando, FL (1984)

    MATH  Google Scholar 

  12. Derflinger, G., Hörmann, W., Leydold, J.: Random variate generation by numerical inversion when only the density is known. ACM Trans. Model. Comput. Simul. 20(18), 1–25 (2010)

    Article  MATH  Google Scholar 

  13. Dingeç, K., Goldsman, D., Alexopoulos, C., Lolos, A., Wilson, J.R.: Geometric-moment contraction, stationary processes, and their indicator processes. Technical report, Gebze Technical University, Georgia Institute of Technology, North Carolina State University (2022). https://people.engr.ncsu.edu/jwilson/files/gmcind-030822.pdf. Accessed 8th Feb 2022

  14. Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4), 987–1007 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  15. Glynn, P.W., Whitt, W.: Estimating the asymptotic variance with batch means. Oper. Res. Lett. 10, 431–435 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  16. Hardy, G.H., Littlewood, J.E., Polya, G.: Inequalities, 2nd edn. Cambridge University Press, Cambridge (1952)

    MATH  Google Scholar 

  17. Keilson, J., Machihara, F.: Hyperexponential waiting time structure in hyperexponential normal upper H Subscript normal upper K Baseline divided by normal upper H Subscript normal upper L Baseline divided by 1\({{\rm H}_{\rm K}/{\rm H}_{\rm L}/1}\) systems. J. Oper. Res. Soc. Jpn. 28(3), 242–251 (1985)

    Google Scholar 

  18. Kingman, J.F.: Inequalities in the theory of queues. J. Roy. Stat. Soc. B 32(1), 102–110 (1970)

    MathSciNet  MATH  Google Scholar 

  19. Li, W.K., Ling, S., McAleer, M.: Recent theoretical results for time series models with GARCH errors. J. Econ. Surv. 16(3), 245–269 (2002)

    Article  Google Scholar 

  20. Mori, M.: Transient behaviour of the mean waiting time and its exact forms in M/M/1 and M/D/1. J. Oper. Res. Soc. Jpn. 19(1), 14–31 (1976)

    MathSciNet  MATH  Google Scholar 

  21. Nicholls, D.F., Quinn, B.G.: Random Coefficient Autoregressive Models: An Introduction. Springer, New York (1982)

    Book  MATH  Google Scholar 

  22. Rolski, T., Schmidli, H., Schmidt, V., Teugels, J.: Stochastic Processes for Insurance and Finance. Wiley, New York (1999)

    Book  MATH  Google Scholar 

  23. Shao, X., Wu, W.B.: Asymptotic spectral theory for nonlinear time series. Ann. Stat. 35(4), 1773–1801 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  24. Tong, H.: Nonlinear Time Series: A Dynamical System Approach. Oxford University Press, New York (1990)

    MATH  Google Scholar 

  25. Wu, W.B.: On the Bahadur representation of sample quantiles for dependent sequences. Ann. Stat. 33(4), 1934–1963 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  26. Wu, W.B., Shao, X.: Limit theorems for iterated random functions. J. Appl. Probab. 41, 425–436 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  27. Wu, W.B., Woodroofe, M.: A central limit theorem for iterated random functions. J. Appl. Probab. 37(3), 748–755 (2000)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

We thank Pierre L’Ecuyer not only for his remarkable contributions to the theory and practice of computer simulation over the past four decades, but also for his equally remarkable contributions as an editor and reviewer in a broad diversity of scientific disciplines, where his work has been applied extensively.

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Correspondence to James R. Wilson .

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Dingeç, K.D., Alexopoulos, C., Goldsman, D., Lolos, A., Wilson, J.R. (2022). Geometric-Moment Contraction of G/G/1 Waiting Times. In: Botev, Z., Keller, A., Lemieux, C., Tuffin, B. (eds) Advances in Modeling and Simulation. Springer, Cham. https://doi.org/10.1007/978-3-031-10193-9_6

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