News:

• The Handbook of Monte Carlo Methods is currently being translated into Japanese. Please contact me or the publisher if you consider a translation into another language.
• I am teaching Mathematical Statistics (STAT3001) in the first semester of 2013. My new book Statistical Modeling and Computation, Springer, to appear late 2013/early 2014, (with Josh Chan from ANU) will be made available to each enrolled student.
• Lecture notes for a graduate course on Monte Carlo methods given at the 2011 Summer School of the Australian Mathematical Science Institute (AMSI). The notes (176 pages) present a highly condensed version of the Handbook (772 pages).
• Try our new kernel density estimator. See also the Annals of Statistics article, which explains how it works.

Publications

• Kroese, D.P. and Botev, Z.I. (2013). Spatial Process Generation. To appear in: V. Schmidt (Ed.). Lectures on Stochastic Geometry, Spatial Statistics and Random Fields, Volume II: Analysis, Modeling and Simulation of Complex Structures, Springer-Verlag, Berlin. (pdf)
• Brereton, T., Chan J.C.C., and Kroese, D.P. (2013). Monte Carlo Methods for Portfolio Credit Risk. To appear in Credit Portfolio Securitizations and Derivatives, H. Scheule and D. Rosch (Eds.), John Wiley & Sons, New York. (pdf)
• Brereton, T., Stenzel, O., Baumeier B., Andienko, D., Schmidt, V., Kroese D. P. (2013). Efficient Simulation of Markov Chains using Segmentation. Methodology and Computing in Applied Probability. DOI 10.1007/s11009-013-9327-x (pdf)
• Stenzel., O, Westhoff, D., Manke, I., Kasper, M., Kroese, D.P., and Schmidt, V. (2013). Graph-based simulated annealing: A hybrid approach to stochastic modeling of complex microstructures. Modelling Simulation Mater. Sci. Eng.. To appear. (pdf)
• Brereton, T., Kroese, D.P., Stenzel, O., Schmidt, Baumeier, B. (2012). Efficient simulation of charge transport in deep-trap media, Proceedings of the 2012 Winter Simulation Conference, C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher, eds. (pdf)
• Kroese, D.P., Rubinstein, R.Y. (2012). Monte Carlo Methods. Wiley Interdisciplinary Reviews: Computational Statistics 4 , 48-58. DOI: 10.1002/wics.194 . (pdf)
• Chan, J.C.C. and Kroese, D.P. (2012). Improved cross-entropy method for estimation. Statistics and Computing 22 (5) 1031--1040. (pdf)
• Brereton, T.I, Chan, J.C.C, and Kroese, D.P. (2011). Fitting mixture importance sampling distributions via improved cross-entropy. Proceedings of the 2011 Winter Simulation Conference. S. Jain, R. R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds., pp. 422--428. (pdf)
• Stacey, K. W. and Kroese, D.P. (2011) Greedy servers on a torus. Proceedings of the 2011 Winter Simulation Conference. S. Jain, R. R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds., pp. 369--380. (pdf)
• Kroese, D.P., Taimre, T., and Botev, Z.I. (2011). Handbook of Monte Carlo Methods, Wiley Series in Probability and Statistics, John Wiley & Sons, New York.
• Kroese, D.P., Rubinstein, R.Y, and Glynn, P.W. (2011). The Cross-Entropy Method for Estimation. In Handbook of Statistics, Volume 31: Machine Learning. V. Govindaraju and C.R. Rao, Eds, North Holland. (pdf)
• Botev, Z.I., Kroese, D.P., Rubinstein, R.Y, and L'Ecuyer, P. (2011). The Cross-Entropy Method for Optimization. In Handbook of Statistics, Volume 31: Machine Learning. V. Govindaraju and C.R. Rao, Eds, North Holland. (pdf)
• Kroese D.P., Rubinstein R. Y., Cohen I., Porotsky S. and T. Taimre "Cross-Entropy Method", in Encyclopedia of Operations Research and Management Sciences, third edition (S. I. Gass and M. C. Fu, Eds.), Springer-Verlag, 2011. (pdf)
• Chan, J.C.C, Glynn P.W., and Kroese, D.P. (2011). A comparison of cross-entropy and variance minimization strategies. Journal of Applied Probability 48A, 183--194. (pdf)
• Botev, Z.I. and Kroese, D.P. (2012). Efficient Monte Carlo simulation via the Generalized Splitting Method. Statistics and Computing. 22 (1), 1--16. (pdf)
• Botev, Z.I., Kroese, D.P. (2011). The Generalized Cross Entropy Method, with Applications to Probability Density Estimation. Methodology and Computing in Applied Probability . 13 (1), 1--27. (pdf)
• Kroese, D.P. (2011). The Cross-Entropy Method. In Wiley Encyclopedia of Operations Research and Management Science J. Cochran, L. A. Cox, Jr., P. Keskinocak, J. P. Kharoufeh, J. C. Smith (Eds.) John Wiley and Sons, New York. (pdf)
• Rojas-Nandayapa, L, Foss, S., and Kroese, D.P. Stability and Performance of Greedy Server Systems: A Review and Open Problems. (2011) Queueing Systems: Theory and Applications 68, 221-227. (pdf)
• Botev, Z.I., Grotowski, J.F, and Kroese, D. P. (2010). Kernel density estimation via diffusion. Annals of Statistics 38 (5), 2916-2957. (pdf) 
• Evans G. E., Sofronov G. Yu., Keith J. M., and Kroese D. P. (2010). Estimating Change-Points in Biological Sequences via the Cross-Entropy Method. Annals of Operations Research. 189 (1), 155--165. (pdf)
• Chan, J.C.C. and Kroese, D.P. (2010). Efficient Estimation of Large Portfolio Loss Probabilities in t-copula Models European Journal of Operational Research, 205 (2), 361--367. (pdf)
• Chan, C. C., Kroese, D.P. (2010). Rare-event Probability Estimation with Conditional Monte Carlo. Annals of Operations Research 189 (1), 43--61. (pdf)
• Kothari, R. P. and Kroese, D.P. (2009). Optimal generation expansion planning via the cross-entropy method. Proceedings of the 2009 Winter Simulation Conference. M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin, and R. G. Ingalls, eds. pp. 1482--1491 (pdf)
• Sofronov G. Yu., Evans G. E., Keith J. M., Kroese D. P. (2009). Identifying Change-points in Biological Sequences via Sequential Importance Sampling. Environmental Modeling & Assessment 14 (5), 577--584. (pdf)
• Belay A., O'Brien, E.G, and Kroese, D.P. (2008). Truck Fleet Model for Design and Assessment of Flexible Pavements. Journal of Sound and Vibration 311 (3--5) 1161--1174.
• Sani, A, Kroese, D.P. (2008). Controling the number of HIV infectives in a mobile population. Mathematical Biosciences 213 103-112. (pdf)
• Botev, Z.I., Kroese, D.P. (2008). An Efficient Algorithm for Rare-event Probability Estimation, Combinatorial Optimization, and Counting. Methodology and Computing in Applied Probability 10 (4), 471--505. (pdf)
• Chan, C.C., Kroese, D.P. (2008). Randomized methods for solving the Winner Determination Problem in combinatorial auctions. Proceedings of the 2008 Winter Simulation Conference, S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds., pp. 1344--1349. (pdf)
• Botev, Z.I., Kroese, D.P. (2008). Non-asymptotic bandwidth selection for density estimation of discrete data. Methodology and Computing in Applied Probability 10 435--451. (ps)
• Keith, J.M., Kroese, D.P. and Sofronov, G. Yu. (2008) Adaptive Independence Samplers. Statistics and Computing. 18 (4) 409--420. (pdf)
• Botev, Z.I, Kroese, D.P., Taimre, T. (2007). Generalized Cross-Entropy Methods with Applications to Rare-Event simulation and Optimization. Simulation 83 (11) 785 - 806.
• Costa, A., Jones, O.D, Kroese, D. P. (2007). Convergence Properties of the Cross-Entropy Method for Discrete Optimization. Operations Research Letters 35 (5), 573-580. (pdf)
• Sani, A. and Kroese, D.P. (2007) Optimal Epidemic Intervention of HIV Spread Using the Cross-Entropy Method. In Kulasiri, D. and Oxley, L. (Eds.) Proceedings of the International Congress on Modelling and Simulation (MODSIM), Modelling and Simulation Society of Australia and New Zealand, pp. 448-454. (pdf)
• Evans, G. , Keith, J.M, Kroese, D.P (2007). Parallel Cross-Entropy Optimization. Proceedings of the 2007 Winter Simulation Conference , Washington DC, pp. 2196-2202. (pdf)

• Rubinstein, R. Y. , Kroese, D. P. (2007). Simulation and the Monte Carlo Method, 2nd edition, Wiley & Sons.
• Rubinstein, R.Y, Kroese, D.P, Dolgin, A. and Glynn, P. W. (2007). Parametric Minimum Cross-Entropy Method for Counting the Number of Satisfiability Assignments. Submitted. (abstract)
• Keith, J.M., Sofronov, G. Yu. and Kroese, D.P. (2007) The Generalized Gibbs Sampler and the Neighborhood Sampler. Proceedings of the 7-th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC 2006) (pdf)
• Kroese, D.P., Nariai, S, Hui, K-P (2007). Network Reliability Optimization via the Cross-Entropy Method. IEEE Trans. Rel. , 56 (2), 275-287. (pdf)
• Sani, A, Kroese, D.P, Pollett, P. (2007). Stochastic Models for the Spread of HIV in a Mobile Heterosexual Population. Mathematical Biosciences 208, 98-124. (pdf)
• Roberts, B., Kroese, D.P. (2007). Estimating the number of s-t paths in a graph. Journal of Graph Algorithms and Applications 11 (1), 195-214. (pdf)
• Kroese, D.P, Rubinstein, R.Y., Taimre, T. (2007). Application of the Cross-Entropy Method to Clustering and Vector Quantization. Journal of Global Optimization 37, 137-157. (pdf)
• Kroese, D.P., Hui, K.-P. (2007). Applications of the Cross-Entropy Method in Reliability. In Computational Intelligence in Reliability Engineering G. Levitin, ed., Springer-Verlag, 37 -- 82. (pdf)
• Botev, Z.I, Kroese, D.P., Taimre, T. (2006). Generalized Cross-Entropy Methods. Proceedings of RESIM06, 1-30. (pdf)
• Sofronov, G, Keith, J.M., Kroese, D.P. (2006). An Optimal Sequential Procedure for a Buying-Selling Problem with Independent Observations. J. Appl. Prob. 43, 454-462 (pdf)
• Asmussen, S., Kroese, D.P. (2006). Improved algorithms for rare event simulation with heavy tails. Advances in Applied Probability 38 (2), 545-558. (pdf)
• Kroese, D.P, Porotsky, S., Rubinstein, R.Y. (2006). The Cross-Entropy Method for Continuous Multi-extremal Optimization. Methodology and Computing in Applied Probability 8, 383--407. (pdf)
• De Boer, P-T., Kroese, D.P, Mannor, S. and Rubinstein, R.Y. (2005). A Tutorial on the Cross-Entropy Method. Annals of Operations Research, 134 (1), 19--67. (pdf)
• Nariai S., Kroese, D.P., Hui, K.P. (2005). Designing an Optimal Network Using the Cross-Entropy Method. In: Lecture Notes in Computer Science: Intelligent Data Engineering and Automated Learning, Gallagher M., Hogan J., Maire F., Eds., Springer-Verlag. Winner of best student paper at IDEAL 2005: 6th International Conference, July 6-8, 2005. pp 228--233 (pdf)
• Nariai S., Kroese, D.P. (2005). On the Design of Multi-type Networks via the Cross-Entropy Method. Proceeding of the Fifth International Workshop on the Design of Reliable Communication Networks (DRCN 2005), pp. 109- 114 (pdf).
• Asmussen, S., Kroese, D.P., Rubinstein, R.Y. (2005). Heavy Tails, Importance Sampling and Cross-Entropy. Stochastic Models 21 (1), 57-76. (postscript)
• Rubinstein, R.Y., Kroese, D.P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning, Springer-Verlag, New York.
• Botev, Z., Kroese, D.P. (2004). Global Likelihood Optimization via the Cross-Entropy Method, with an Application to Mixture Models. Proceedings of the Winter Simulation Conference, Washington DC, pp 529--535. (pdf)
• Keith, J., Kroese, D.P., Bryant, D. (2004). A Generalized Markov Chain Sampler. Methodology and Computing in Applied Probability, 6 (1) 29-53. (pdf)
• Hui, K-P., Bean, N, Kraetzl, M and Kroese, D.P. (2005). The Cross-Entropy Method for Network Reliability Estimation. Annals of Operations Research, 134 (1), 101--118. (pdf)
• Kroese, D.P. (2005). Review of Kernel Methods for pattern Analysis, SIAM Review, 47 (2), 385-387.
• Alon, G., Kroese, D.P., Raviv, T. and Rubinstein, R.Y. (2005). Application of the Cross-Entropy Method to the Buffer Allocation Problem in a Simulation-Based Environment. Annals of Operations Research, 134 (1), 137--151. (pdf)
• De Boer, P.-T., Kroese, D.P., Rubinstein, R.Y. (2004). A Fast Cross-Entropy Method for Estimating Buffer Overflows in Queueing Networks. Management Science, 50 (7), pp 883--895. (pdf)
• Kroese, D.P. and Rubinstein, R.Y. (2004). The Transform Likelihood Ratio Method for Rare Event Simulation with Heavy Tails. Queueing Systems, 46, pp 317--351. (postscript)
• Kroese, D.P., Scheinhardt, W.C.W. and Taylor, P.G. (2004). Spectral Properties of the Tandem Jackson Network, Seen as a Quasi-Birth-and-Death Process. Annals of Applied Probability 14 (4), pp 2057--2089. (pdf)
• Hui, K-P., Bean, N., Kraetzl, M. and Kroese, D.P. (2003). The Tree Cut and Merge Algorithm for Estimation of Network Reliability. Probability in the Engineering and Informational Sciences 17 23-45. Available on-line at Cambridge Journals.
• Hui, K-P., Bean, N, Kraetzl, M and Kroese, D.P. (2003). Network Reliability Estimation Using the Tree Cut and Merge Algorithm with Importance Sampling. Proceeding of the Fourth International Workshop on the Design of Reliable Communication Networks (DRCN 2003), pp. 254 - 262.
• Keith J.M., , Adams P. , Bryant D., Kroese D.P., Mitchelson K.R., Cochran D.A.E. and Lala G.H. (2002). A Simulated Annealing Algorithm for Finding Consensus Sequences. Bioinformatics 18 1494-1499.
• Garvels, M.J.J., Kroese, D.P., Van Ommeren J-K.C.W. (2002). On the importance function in splitting simulation. European Transactions on Telecommunications 13 (4) 363-371 (postscript)
• Kroese, D.P., Nicola V.F. (2002). Efficient Simulation of a Tandom Jackson Network. ACM Transactions on Modeling and Computer Simulation 12 (2), 199-141. (postscript)
• Keith, J., Kroese, D.P. (2002). Sequence Alignment By Rare Event Simulation. Proceedings of the 2002 Winter Simulation Conference , San Diego, 320 - 327. (pdf)
• De Boer, P.-T., Kroese, D.P., Rubinstein, R.Y. (2002). Estimating Buffer Overflows in Three Stages using Cross-Entropy Proceedings of the 2002 Winter Simulation Conference , San Diego, 301 - 309.
• Kroese, D.P., Scheinhardt, W.R.W. (2001). Joint distributions for interacting fluid queues. Queueing Systems, special issue on Stochastic Models with Tractable Steady State Characteristics, 37, 99-140. (postscript)
• Kroese, D.P. (2000). On the decay rates of buffers in continuous flow lines. Methodology and Computing in Applied Probability, 2, 425-441. (postscript)
• Kroese, D.P., Nicola V.F. (1999). Efficient estimation of overflow probabilities in queues with breakdowns. Performance Evaluation, 36-37 471-484. (postscript)
• Kroese, D.P., Nicola, V.F. (1998). Efficient simulation of backlogs in fluid flow lines, Int. J. Electron. Commun. (AEU) 52 (3), pp. 165-171.(postscript)
• Garvels, M.J.J., Kroese, D.P. (1998). A comparison of RESTART implementations. Proceedings of the Winter Simulation Conference , Washington, pp.601-609. (postscript)
• Kroese, D.P., Scheinhardt, W.R.W. (1998). A fluid queue driven by a fluid queue. In B. Goldstein, A. Koucheryavy and M. Shneps-Shneppe, editors, Teletraffic theory as a base for QoS: monitoring, evaluation, decisions, 389-400, St. Petersburg. (postscript)
• Kroese, D.P. (1997). Heavy-traffic analysis for continuous polling models, J. Appl. Probab. 34, pp. 720-732. (postscript)
• Kroese, D.P. , Schmidt, V. (1996). Light-traffic Analysis for Queues with Spatially Distributed Arrivals. Math. of O.R. 21 (1) 135-157.

• Kroese, D.P. , Schmidt, V. (1994). Single-Server Queues with Spatially Distributed Arrivals. Queueing Systems 17 (I-II) 317-345.
• Kroese, D.P. , Schmidt, V. (1993). Queueing Systems on a Circle. Zeitschrift f. Operations Res. 37 303-331.
• Kroese, D.P. , Schmidt, V. (1992). A Continuous Polling System with General Service Times. Ann. Appl. Prob. 2 906-927.
• Kroese, D.P. , Kallenberg, W.C.M. (1992). Second-order Asymptotics in Level Crossing for Differences of Renewal Processes. Stochastic Processes 40 309-323.
• Kroese, D.P. (1992). The Difference of Two Renewal Processes. Level Crossing and the Infimum. Stochastic Models 8 (2) 221-243.
• Kroese, D.P. , Kallenberg, W.C.M. (1989). Approximations to the Lifetime distribution of k-out-of-n Systems with Cold Standby. Math. of O.R. 14 (3) 485-501.