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Importance Sampling for Stochastic Simulations

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Cited by:

  1. Mandjes, M., 1993. "Fast simulation of Markov fluid models in conjunction with large deviations," Serie Research Memoranda 0058, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  2. Kuruganti, I. & Strickland, S., 1997. "Optimal importance sampling for Markovian systems with applications to tandem queues," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 44(1), pages 61-79.
  3. N. Hilber & N. Reich & C. Schwab & C. Winter, 2009. "Numerical methods for Lévy processes," Finance and Stochastics, Springer, vol. 13(4), pages 471-500, September.
  4. Kriman, V. & Rubinstein, R.Y., 1995. "Polynomial Time Algorithms for Estimation of Rare Events in Queueing Models," Discussion Paper 1995-12, Tilburg University, Center for Economic Research.
  5. Hernan P. Awad & Peter W. Glynn & Reuven Y. Rubinstein, 2013. "Zero-Variance Importance Sampling Estimators for Markov Process Expectations," Mathematics of Operations Research, INFORMS, vol. 38(2), pages 358-388, May.
  6. Bosetti, Valentina & Marangoni, Giacomo & Borgonovo, Emanuele & Diaz Anadon, Laura & Barron, Robert & McJeon, Haewon C. & Politis, Savvas & Friley, Paul, 2015. "Sensitivity to energy technology costs: A multi-model comparison analysis," Energy Policy, Elsevier, vol. 80(C), pages 244-263.
  7. Hsieh, Ming-Hua & Lee, Yi-Hsi & Shyu, So-De & Chiu, Yu-Fen, 2019. "Estimating multifactor portfolio credit risk: A variance reduction approach," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
  8. Philippe Jehiel & Jakub Steiner, 2020. "Selective Sampling with Information-Storage Constraints [On interim rationality, belief formation and learning in decision problems with bounded memory]," The Economic Journal, Royal Economic Society, vol. 130(630), pages 1753-1781.
  9. Helton, J.C. & Johnson, J.D. & Oberkampf, W.L., 2007. "Verification test problems for the calculation of probability of loss of assured safety in temperature-dependent systems with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1374-1387.
  10. Mulvey, John M. & Rosenbaum, Daniel P. & Shetty, Bala, 1997. "Strategic financial risk management and operations research," European Journal of Operational Research, Elsevier, vol. 97(1), pages 1-16, February.
  11. Fodstad, Marte & Crespo del Granado, Pedro & Hellemo, Lars & Knudsen, Brage Rugstad & Pisciella, Paolo & Silvast, Antti & Bordin, Chiara & Schmidt, Sarah & Straus, Julian, 2022. "Next frontiers in energy system modelling: A review on challenges and the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  12. Barry L. Nelson, 2004. "50th Anniversary Article: Stochastic Simulation Research in Management Science," Management Science, INFORMS, vol. 50(7), pages 855-868, July.
  13. Sandeep Juneja & Perwez Shahabuddin, 2001. "Fast Simulation of Markov Chains with Small Transition Probabilities," Management Science, INFORMS, vol. 47(4), pages 547-562, April.
  14. Franks, Jordan & Vihola, Matti, 2020. "Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 6157-6183.
  15. Helton, J.C. & Hansen, C.W. & Sallaberry, C.J., 2014. "Conceptual structure and computational organization of the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 223-248.
  16. Helton, J.C. & Johnson, J.D. & Oberkampf, W.L., 2006. "Probability of loss of assured safety in temperature dependent systems with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 91(3), pages 320-348.
  17. Torrisi, G. L., 2004. "Simulating the ruin probability of risk processes with delay in claim settlement," Stochastic Processes and their Applications, Elsevier, vol. 112(2), pages 225-244, August.
  18. Morio, Jérôme & Jacquemart, Damien & Balesdent, Mathieu & Marzat, Julien, 2013. "Optimisation of interacting particle systems for rare event estimation," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 117-128.
  19. Francesco Strino & Fabio Parisi & Yuval Kluger, 2011. "VDA, a Method of Choosing a Better Algorithm with Fewer Validations," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-8, October.
  20. Youngjun Choe & Henry Lam & Eunshin Byon, 2018. "Uncertainty Quantification of Stochastic Simulation for Black-box Computer Experiments," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1155-1172, December.
  21. T. P. I. Ahamed & V. S. Borkar & S. Juneja, 2006. "Adaptive Importance Sampling Technique for Markov Chains Using Stochastic Approximation," Operations Research, INFORMS, vol. 54(3), pages 489-504, June.
  22. Frikha Noufel & Sagna Abass, 2012. "Quantization based recursive importance sampling," Monte Carlo Methods and Applications, De Gruyter, vol. 18(4), pages 287-326, December.
  23. Nam Kyoo Boots & Perwez Shahabuddin, 2001. "Simulating Tail Probabilities in GI/GI.1 Queues and Insurance Risk Processes with Subexponentail Distributions," Tinbergen Institute Discussion Papers 01-012/4, Tinbergen Institute.
  24. Kaynar, Bahar & Ridder, Ad, 2010. "The cross-entropy method with patching for rare-event simulation of large Markov chains," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1380-1397, December.
  25. Cheng-Der Fuh & Yanwei Jia & Steven Kou, 2023. "A General Framework for Importance Sampling with Latent Markov Processes," Papers 2311.12330, arXiv.org.
  26. H. Zhong & P. van Gelder & P. van Overloop & W. Wang, 2014. "Application of a fast stochastic storm surge model on estimating the high water level frequency in the Lower Rhine Delta," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 743-759, September.
  27. Kleijnen, J.P.C., 1997. "Experimental Design for Sensitivity Analysis, Optimization and Validation of Simulation Models," Discussion Paper 1997-52, Tilburg University, Center for Economic Research.
  28. Steiner, Jakub & Jehiel, Philippe, 2017. "On Second Thoughts, Selective Memory, and Resulting Behavioral Biases," CEPR Discussion Papers 12546, C.E.P.R. Discussion Papers.
  29. Marvin K. Nakayama & Perwez Shahabuddin, 1998. "Likelihood Ratio Derivative Estimation for Finite-Time Performance Measures in Generalized Semi-Markov Processes," Management Science, INFORMS, vol. 44(10), pages 1426-1441, October.
  30. Tito Homem-de-Mello, 2007. "A Study on the Cross-Entropy Method for Rare-Event Probability Estimation," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 381-394, August.
  31. Paul Glasserman & Jeremy Staum, 2001. "Conditioning on One-Step Survival for Barrier Option Simulations," Operations Research, INFORMS, vol. 49(6), pages 923-937, December.
  32. Pierre L’Ecuyer & Bruno Tuffin, 2011. "Approximating zero-variance importance sampling in a reliability setting," Annals of Operations Research, Springer, vol. 189(1), pages 277-297, September.
  33. N-H Shih, 2005. "Estimating completion-time distribution in stochastic activity networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 744-749, June.
  34. Meng Lu & Jie Zhang & Qing Lü & Lulu Zhang, 2023. "Assessing the annual probability of rainfall-induced slope failure based on intensity–duration–frequency (IDF) curves," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(1), pages 763-778, May.
  35. Prusty, B Rajanarayan & Jena, Debashisha, 2017. "A critical review on probabilistic load flow studies in uncertainty constrained power systems with photovoltaic generation and a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1286-1302.
  36. Pierre Rostan & Alexandra Rostan & François-Éric Racicot, 2020. "Increment Variance Reduction Techniques with an Application to Multi-name Credit Derivatives," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 1-35, January.
  37. Papadopoulos C., 1998. "A New Technique for MTTF Estimation in Highly Reliable Markovian Systems," Monte Carlo Methods and Applications, De Gruyter, vol. 4(2), pages 95-112, December.
  38. Samet, Haidar & Khorshidsavar, Morteza, 2018. "Analytic time series load flow," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3886-3899.
  39. Helton, Jon C. & Sallaberry, Cedric J., 2009. "Computational implementation of sampling-based approaches to the calculation of expected dose in performance assessments for the proposed high-level radioactive waste repository at Yucca Mountain, Nev," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 699-721.
  40. Fakhouri H. & Nasroallah A., 2009. "On the simulation of Markov chain steady-state distribution using CFTP algorithm," Monte Carlo Methods and Applications, De Gruyter, vol. 15(2), pages 91-105, January.
  41. 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.
  42. Kriman, V. & Rubinstein, R.Y., 1995. "Polynomial Time Algorithms for Estimation of Rare Events in Queueing Models," Other publications TiSEM bb044e22-c7f1-41f2-b4d9-2, Tilburg University, School of Economics and Management.
  43. Matti Vihola & Jouni Helske & Jordan Franks, 2020. "Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1339-1376, December.
  44. Ming-Tao CHUNG & Ming-Hua HSIEH & Yan-Ping CHI, 2017. "Computation of Operational Risk for Financial Institutions," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 77-87, September.
  45. Xie, Junfei & Wan, Yan & Mills, Kevin & Filliben, James J. & Lei, Yu & Lin, Zongli, 2019. "M-PCM-OFFD: An effective output statistics estimation method for systems of high dimensional uncertainties subject to low-order parameter interactions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 93-118.
  46. Ridder, A., 1993. "Fast simulation of Markov fluid models," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  47. Dassios, Angelos & Jang, Jiwook & Zhao, Hongbiao, 2015. "A risk model with renewal shot-noise Cox process," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 55-65.
  48. Dantzig, George B. & Infanger, Gerd, 1997. "Intelligent control and optimization under uncertainty with application to hydro power," European Journal of Operational Research, Elsevier, vol. 97(2), pages 396-407, March.
  49. Basrak, Bojan & Conroy, Michael & Olvera-Cravioto, Mariana & Palmowski, Zbigniew, 2022. "Importance sampling for maxima on trees," Stochastic Processes and their Applications, Elsevier, vol. 148(C), pages 139-179.
  50. Mulvey, John M. & Rosenbaum, Daniel P. & Shetty, Bala, 1999. "Parameter estimation in stochastic scenario generation systems," European Journal of Operational Research, Elsevier, vol. 118(3), pages 563-577, November.
  51. Søren Asmussen & Reuven Y. Rubinstein, 1999. "Sensitivity Analysis of Insurance Risk Models via Simulation," Management Science, INFORMS, vol. 45(8), pages 1125-1141, August.
  52. Bahar Kaynar & Ad Ridder, 2009. "The Cross-Entropy Method with Patching for Rare-Event Simulation of Large Markov Chains," Tinbergen Institute Discussion Papers 09-084/4, Tinbergen Institute.
  53. Stern, R.E. & Song, J. & Work, D.B., 2017. "Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 1-9.
  54. Dassios, Angelos & Jang, Jiwook & Zhao, Hongbiao, 2015. "A risk model with renewal shot-noise Cox process," LSE Research Online Documents on Economics 64051, London School of Economics and Political Science, LSE Library.
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