IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v116y1999i3p681-691.html
   My bibliography  Save this article

Student t-tests and compound tests to detect transients in simulated time series

Author

Listed:
  • Ockerman, Daniel H.
  • Goldsman, David

Abstract

No abstract is available for this item.

Suggested Citation

  • Ockerman, Daniel H. & Goldsman, David, 1999. "Student t-tests and compound tests to detect transients in simulated time series," European Journal of Operational Research, Elsevier, vol. 116(3), pages 681-691, August.
  • Handle: RePEc:eee:ejores:v:116:y:1999:i:3:p:681-691
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(98)00233-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gamze Tokol & David Goldsman & Daniel H. Ockerman & James J. Swain, 1998. "Standardized Time Series Lp-Norm Variance Estimators for Simulations," Management Science, INFORMS, vol. 44(2), pages 234-245, February.
    2. Lee W. Schruben, 1982. "Detecting Initialization Bias in Simulation Output," Operations Research, INFORMS, vol. 30(3), pages 569-590, June.
    3. Philip Heidelberger & Peter D. Welch, 1983. "Simulation Run Length Control in the Presence of an Initial Transient," Operations Research, INFORMS, vol. 31(6), pages 1109-1144, December.
    4. Ward Whitt, 1989. "Planning Queueing Simulations," Management Science, INFORMS, vol. 35(11), pages 1341-1366, November.
    5. Lee Schruben, 1983. "Confidence Interval Estimation Using Standardized Time Series," Operations Research, INFORMS, vol. 31(6), pages 1090-1108, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. K Hoad & S Robinson & R Davies, 2010. "Automating warm-up length estimation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(9), pages 1389-1403, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gamze Tokol & David Goldsman & Daniel H. Ockerman & James J. Swain, 1998. "Standardized Time Series Lp-Norm Variance Estimators for Simulations," Management Science, INFORMS, vol. 44(2), pages 234-245, February.
    2. Koning, A.J., 1999. "Goodness of fit for the constancy of a classical statistical model over time," Econometric Institute Research Papers EI 9959-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Halkos, George & Kevork, Ilias, 2002. "Confidence intervals in stationary autocorrelated time series," MPRA Paper 31840, University Library of Munich, Germany.
    4. Sheth-Voss, Pieter A. & Willemain, Thomas R. & Haddock, Jorge, 2005. "Estimating the steady-state mean from short transient simulations," European Journal of Operational Research, Elsevier, vol. 162(2), pages 403-417, April.
    5. Halkos, George & Kevork, Ilias, 2006. "Estimating population means in covariance stationary process," MPRA Paper 31843, University Library of Munich, Germany.
    6. Enver Yücesan, 1993. "Randomization tests for initialization bias in simulation output," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(5), pages 643-663, August.
    7. Song, Wheyming Tina, 1996. "On the estimation of optimal batch sizes in the analysis of simulation output," European Journal of Operational Research, Elsevier, vol. 88(2), pages 304-319, January.
    8. David F. Muñoz & Peter W. Glynn, 2001. "Multivariate Standardized Time Series for Steady-State Simulation Output Analysis," Operations Research, INFORMS, vol. 49(3), pages 413-422, June.
    9. David Goldsman & Keebom Kang & Andrew F. Seila, 1999. "Cramér-von Mises Variance Estimators for Simulations," Operations Research, INFORMS, vol. 47(2), pages 299-309, April.
    10. James M. Calvin & Marvin K. Nakayama, 2006. "Permuted Standardized Time Series for Steady-State Simulations," Mathematics of Operations Research, INFORMS, vol. 31(2), pages 351-368, May.
    11. Halim Damerdji & David Goldsman, 1995. "Consistency of several variants of the standardized time series area variance estimator," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(8), pages 1161-1176, December.
    12. David Goldsman & Lee W. Schruben & James J. Swain, 1994. "Tests for transient means in simulated time series," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(2), pages 171-187, March.
    13. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    14. Lada, Emily K. & Wilson, James R., 2006. "A wavelet-based spectral procedure for steady-state simulation analysis," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1769-1801, November.
    15. Guangwu Liu & Liu Jeff Hong, 2009. "Kernel estimation of quantile sensitivities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(6), pages 511-525, September.
    16. Riccardo (Jack) Lucchetti & Luca Pedini, 2020. "ParMA: Parallelised Bayesian Model Averaging for Generalised Linear Models," Working Papers 2020:28, Department of Economics, University of Venice "Ca' Foscari".
    17. Goldman Elena & Tsurumi Hiroki, 2005. "Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-38, June.
    18. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    19. Michael Edwards, 2010. "A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 75(3), pages 474-497, September.
    20. David Goldsman & Keebom Kang & Seong‐Hee Kim & Andrew F. Seila & Gamze Tokol, 2007. "Combining standardized time series area and Cramér–von Mises variance estimators," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 384-396, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:116:y:1999:i:3:p:681-691. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.