IDEAS home Printed from https://ideas.repec.org/p/tiu/tiurem/25aee5db-38eb-4e05-b032-2f126e4e4b09.html
   My bibliography  Save this paper

Sensitivity analysis of simulation experiments : Regression analysis and statistical design

Author

Listed:
  • Kleijnen, J.P.C.

    (Tilburg University, Faculty of Economics)

Abstract

This tutorial gives a survey of strategic issues in the statistical design and analysis of experiments with deterministic and random simulation models. These issues concern validation, what-if analysis, optimization, and so on. The analysis uses regression models and least-squares algorithms. The design uses classical experimental designs such as 2k−p factorials, which are more efficient than one at a time designs are. Moreover, classical designs make it possible to estimate interactions among inputs to the simulation. Simulation models may be optimized through response surface methodology, which combines steepest ascent with regression analysis and experimental design. If there are very many inputs, then special techniques such as group screening and sequential bifurcation are useful. Several applications are discussed.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Kleijnen, J.P.C., 1990. "Sensitivity analysis of simulation experiments : Regression analysis and statistical design," Research Memorandum FEW 440, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiurem:25aee5db-38eb-4e05-b032-2f126e4e4b09
    as

    Download full text from publisher

    File URL: https://pure.uvt.nl/ws/portalfiles/portal/1136531/KJ5617894.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kleijnen, J.P.C., 1990. "Statistics and deterministic simulation models : Why not?," Research Memorandum FEW 435, Tilburg University, School of Economics and Management.
    2. Kleijnen, J.P.C., 1988. "Simulation and optimization in production planning : A case study (Version 2)," Research Memorandum FEW 308, Tilburg University, School of Economics and Management.
    3. R. W. Conway, 1963. "Some Tactical Problems in Digital Simulation," Management Science, INFORMS, vol. 10(1), pages 47-61, October.
    4. Kleijnen, Jack P. C. & Standridge, Charles R., 1988. "Experimental design and regression analysis in simulation: An FMS case study," European Journal of Operational Research, Elsevier, vol. 33(3), pages 257-261, February.
    5. Bettonvil, B.W.M. & Kleijnen, J.P.C., 1991. "Identifying the important factors in simulation models with many factors," Research Memorandum FEW 498, Tilburg University, School of Economics and Management.
    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. Reis dos Santos, M. Isabel & Reis dos Santos, Pedro M., 2016. "Switching regression metamodels in stochastic simulation," European Journal of Operational Research, Elsevier, vol. 251(1), pages 142-147.
    2. Backus, G. B. C. & Timmer, G. Th. & Dijkhuizen, A. A. & Eidman, V. R. & Vos, F., 1995. "A decision support system for strategic planning on pig farms," Agricultural Economics, Blackwell, vol. 13(2), pages 101-108, November.
    3. Storlie, Curtis B. & Helton, Jon C., 2008. "Multiple predictor smoothing methods for sensitivity analysis: Description of techniques," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 28-54.
    4. Salameh, F. & Picot, A. & Chabert, M. & Maussion, P., 2017. "Regression methods for improved lifespan modeling of low voltage machine insulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 200-216.
    5. Helton, Jon C. & Hansen, Clifford W. & Sallaberry, Cédric J., 2012. "Uncertainty and sensitivity analysis in performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 44-63.
    6. Helton, Jon C., 2011. "Quantification of margins and uncertainties: Conceptual and computational basis," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 976-1013.
    7. Huyet, A.L., 2006. "Optimization and analysis aid via data-mining for simulated production systems," European Journal of Operational Research, Elsevier, vol. 173(3), pages 827-838, September.
    8. Graham, Tennille & White, Benedict & Pannell, David J., 2003. "Efficiency Policies for Salinity Management: Preliminary Research from a Spatial and Dynamic Metamodel," 2003 Conference (47th), February 12-14, 2003, Fremantle, Australia 57879, Australian Agricultural and Resource Economics Society.
    9. Pannell, David J., 1997. "Sensitivity analysis of normative economic models: theoretical framework and practical strategies," Agricultural Economics, Blackwell, vol. 16(2), pages 139-152, May.
    10. Graham, Tennille, 2005. "On the Road to Better Management: An investigation into the benefits of managing the impacts of dryland salinity on roads," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137921, Australian Agricultural and Resource Economics Society.
    11. Priyanka Majumder & Arnab Paul & Pratik Saha & Mrinmoy Majumder & Dayarnab Baidya & Dhritiman Saha, 2023. "Trapezoidal fuzzy BWM-TOPSIS approach and application on water resources," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(3), pages 2648-2669, March.
    12. Sallaberry, C.J. & Helton, J.C. & Hora, S.C., 2008. "Extension of Latin hypercube samples with correlated variables," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 1047-1059.
    13. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    14. Bozağaç, Doruk & Batmaz, İnci & Oğuztüzün, Halit, 2016. "Dynamic simulation metamodeling using MARS: A case of radar simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 124(C), pages 69-86.
    15. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    16. Tilottama Chakraborty & Mrinmoy Majumder, 2019. "Application of statistical charts, multi-criteria decision making and polynomial neural networks in monitoring energy utilization of wave energy converters," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(1), pages 199-219, February.
    17. Soumya Ghosh & Mrinmoy Majumder & Manish Pal, 2018. "Application of metaheuristic algorithm to identify priority parameters for the selection of feasible location having optimum wave energy potential," Energy & Environment, , vol. 29(1), pages 3-28, February.

    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. Kleijnen, J.P.C., 1995. "Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments," Other publications TiSEM 87ee6ee0-592c-4204-ac50-6, Tilburg University, School of Economics and Management.
    2. Kleijnen, J.P.C., 2006. "Regression Models and Experimental Designs : A Tutorial for Simulation Analaysts," Other publications TiSEM 7b8ecddb-f49e-4b80-865b-a, Tilburg University, School of Economics and Management.
    3. Kleijnen, J.P.C., 1995. "Statistical validation of simulation models : A case study," Other publications TiSEM 4da192cf-c3f4-40a4-aea4-5, Tilburg University, School of Economics and Management.
    4. van Groenendaal, Willem J. H., 1998. "Estimating NPV variability for deterministic models," European Journal of Operational Research, Elsevier, vol. 107(1), pages 202-213, May.
    5. Durieux, Severine & Pierreval, Henri, 2004. "Regression metamodeling for the design of automated manufacturing system composed of parallel machines sharing a material handling resource," International Journal of Production Economics, Elsevier, vol. 89(1), pages 21-30, May.
    6. Mingchang Chih, 2019. "An Insight into the Data Structure of the Dynamic Batch Means Algorithm with Binary Tree Code," Mathematics, MDPI, vol. 7(9), pages 1-8, August.
    7. Jin, Ding & Hedtrich, Johannes & Henning, Christian, 2018. "Applying Meta modeling for extended CGE-modeling: Sample techniques and potential application," Conference papers 332947, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    8. Vinod, V. & Sridharan, R., 2011. "Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system," International Journal of Production Economics, Elsevier, vol. 129(1), pages 127-146, January.
    9. Song, Wheyming Tina & Chih, Mingchang, 2013. "Run length not required: Optimal-mse dynamic batch means estimators for steady-state simulations," European Journal of Operational Research, Elsevier, vol. 229(1), pages 114-123.
    10. 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.
    11. Kleijnen, J.P.C. & Alink, G.A., 1992. "Validation of simulation models : Mine-hunting case-study," Other publications TiSEM 7158fbd4-2932-4cc9-8c10-5, Tilburg University, School of Economics and Management.
    12. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    13. Kleijnen, Jack P. C., 1995. "Statistical validation of simulation models," European Journal of Operational Research, Elsevier, vol. 87(1), pages 21-34, November.
    14. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    15. Kleijnen, Jack P. C. & Sargent, Robert G., 2000. "A methodology for fitting and validating metamodels in simulation," European Journal of Operational Research, Elsevier, vol. 120(1), pages 14-29, January.
    16. Ilan Halachmi & Yitzhak Simon & Noam Mozes, 2014. "Simulation of the shift from marine netcages to inland recirculating aquaculture systems," Annals of Operations Research, Springer, vol. 219(1), pages 85-99, August.
    17. Halkos, George & Kevork, Ilias, 2002. "Confidence intervals in stationary autocorrelated time series," MPRA Paper 31840, University Library of Munich, Germany.
    18. Garcia, Rosanna & Rummel, Paul & Hauser, John, 2007. "Validating agent-based marketing models through conjoint analysis," Journal of Business Research, Elsevier, vol. 60(8), pages 848-857, August.
    19. Crawford, J. W. & Gallwey, T. J., 2000. "Bias and variance reduction in computer simulation studies," European Journal of Operational Research, Elsevier, vol. 124(3), pages 571-590, August.
    20. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.

    More about this item

    Keywords

    Simulation; mathematische statistiek;

    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:tiu:tiurem:25aee5db-38eb-4e05-b032-2f126e4e4b09. 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: Richard Broekman (email available below). General contact details of provider: https://www.tilburguniversity.edu/about/schools/economics-and-management/ .

    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.