IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/8068.html
   My bibliography  Save this paper

A general framework for statistical inference on discrete event systems

Author

Listed:
  • Nicolai, R.P.
  • Koning, A.J.

Abstract

We present a framework for statistical analysis of discrete event systems which combines tools such as simulation of marked point processes, likelihood methods, kernel density estimation and stochastic approximation to enable statistical analysis of the discrete event system, even if conventional approaches fail due to the mathematical intractability of the model. The approach is illustrated with an application to modelling and estimating corrosion of steel gates in the Dutch Haringvliet storm surge barrier.

Suggested Citation

  • Nicolai, R.P. & Koning, A.J., 2006. "A general framework for statistical inference on discrete event systems," Econometric Institute Research Papers EI 2006-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:8068
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/8068/EI2006-45.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicolai, Robin P. & Dekker, Rommert & van Noortwijk, Jan M., 2007. "A comparison of models for measurable deterioration: An application to coatings on steel structures," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1635-1650.
    2. Nathan L. Kleinman & James C. Spall & Daniel Q. Naiman, 1999. "Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers," Management Science, INFORMS, vol. 45(11), pages 1570-1578, November.
    3. Sigrún Andradöttir, 1996. "A Scaled Stochastic Approximation Algorithm," Management Science, INFORMS, vol. 42(4), pages 475-498, April.
    4. Tarn Duong & Martin L. Hazelton, 2005. "Cross‐validation Bandwidth Matrices for Multivariate Kernel Density Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(3), pages 485-506, September.
    Full references (including those not matched with items on IDEAS)

    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. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2012. "Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 732-740.
    2. Billings, Stephen B. & Johnson, Erik B., 2012. "A non-parametric test for industrial specialization," Journal of Urban Economics, Elsevier, vol. 71(3), pages 312-331.
    3. Boris Branisa & Adriana Cardozo, 2009. "Regional Growth Convergence in Colombia Using Social Indicators," Ibero America Institute for Econ. Research (IAI) Discussion Papers 195, Ibero-America Institute for Economic Research.
    4. Nicolai, R.P. & Frenk, J.B.G. & Dekker, R., 2007. "Modelling and Optimizing Imperfect Maintenance of Coatings on Steel Structures," ERIM Report Series Research in Management ERS-2007-043-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Guillermo Durand & Fernando Mele & J. Bandoni, 2012. "Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties," Annals of Operations Research, Springer, vol. 199(1), pages 225-247, October.
    6. M D Pandey & T Cheng & J A M van der Weide, 2011. "Finite-time maintenance cost analysis of engineering systems affected by stochastic degradation," Journal of Risk and Reliability, , vol. 225(2), pages 241-250, June.
    7. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    8. Chen, Shih-Pin, 2007. "Solving fuzzy queueing decision problems via a parametric mixed integer nonlinear programming method," European Journal of Operational Research, Elsevier, vol. 177(1), pages 445-457, February.
    9. Seppo Pulkkinen & Marko Mäkelä & Napsu Karmitsa, 2013. "A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates," Journal of Global Optimization, Springer, vol. 56(2), pages 459-487, June.
    10. Yan, Hanhuan & Han, Liyan, 2019. "Empirical distributions of stock returns: Mixed normal or kernel density?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 473-486.
    11. C Meier-Hirmer & G Riboulet & F Sourget & M Roussignol, 2009. "Maintenance optimization for a system with a gamma deterioration process and intervention delay: Application to track maintenance," Journal of Risk and Reliability, , vol. 223(3), pages 189-198, September.
    12. Filippone, Maurizio & Sanguinetti, Guido, 2011. "Approximate inference of the bandwidth in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3104-3122, December.
    13. Cárdenas-Gallo, Iván & Sarmiento, Carlos A. & Morales, Gilberto A. & Bolivar, Manuel A. & Akhavan-Tabatabaei, Raha, 2017. "An ensemble classifier to predict track geometry degradation," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 53-60.
    14. Pulkkinen, Seppo, 2015. "Ridge-based method for finding curvilinear structures from noisy data," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 89-109.
    15. Stephen E. Chick & Yaozhong Wu, 2005. "Selection Procedures with Frequentist Expected Opportunity Cost Bounds," Operations Research, INFORMS, vol. 53(5), pages 867-878, October.
    16. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    17. Maik Eisenbeiss & Goran Kauermann & Willi Semmler, 2007. "Estimating Beta-Coefficients of German Stock Data: A Non-Parametric Approach," The European Journal of Finance, Taylor & Francis Journals, vol. 13(6), pages 503-522.
    18. J. Chacón & T. Duong, 2010. "Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(2), pages 375-398, August.
    19. Schoch, Tobias & Staub, Kaspar & Pfister, Christian, 2012. "Social inequality and the biological standard of living: An anthropometric analysis of Swiss conscription data, 1875–1950," Economics & Human Biology, Elsevier, vol. 10(2), pages 154-173.
    20. Kao, Chiang & Chen, Shih-Pin, 2006. "A stochastic quasi-Newton method for simulation response optimization," European Journal of Operational Research, Elsevier, vol. 173(1), pages 30-46, August.

    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:ems:eureir:8068. 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: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.html .

    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.