Select Publications

Books

Kroese DP;Taimre T;Botev ZI, 2011, Handbook of Monte Carlo Methods, http://dx.doi.org/10.1002/9781118014967

Kroese D;Taimre T;Botev Z;Rubinstein RY, 2007, Solutions Manual for Monte Carlo Methods, 2nd, Wiley-Interscience

Book Chapters

Kroese DP;Botev ZI, 2015, 'Spatial process simulation', in Lecture Notes in Mathematics, pp. 369 - 404, http://dx.doi.org/10.1007/978-3-319-10064-7_12

Journal articles

Botev ZI, 2017, 'The normal law under linear restrictions: simulation and estimation via minimax tilting', Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 79, pp. 125 - 148, http://dx.doi.org/10.1111/rssb.12162

Botev ZI;Ridder A;Rojas-Nandayapa L, 2016, 'Semiparametric cross entropy for rare-event simulation', Journal of Applied Probability, vol. 53, pp. 633 - 649, http://dx.doi.org/10.1017/jpr.2016.31

Vaisman R;Botev ZI;Ridder A, 2016, 'Sequential Monte Carlo for counting vertex covers in general graphs', Statistics and Computing, vol. 26, pp. 591 - 607, http://dx.doi.org/10.1007/s11222-015-9546-9

Botev ZI;L'Ecuyer P;Simard R;Tuffin B, 2016, 'Static Network Reliability Estimation under the Marshall-Olkin Copula', ACM Transactions on Modeling and Computer Simulation, vol. 26, http://dx.doi.org/10.1145/2775106

Botev ZI;Lloyd CJ, 2015, 'Importance accelerated robbins-monro recursion with applications to parametric confidence limits', Electronic Journal of Statistics, vol. 9, pp. 2058 - 2075, http://dx.doi.org/10.1214/15-EJS1071

Kroese DP;Brereton T;Taimre T;Botev ZI, 2014, 'Why the Monte Carlo method is so important today', Wiley Interdisciplinary Reviews: Computational Statistics, vol. 6, pp. 386 - 392, http://dx.doi.org/10.1002/wics.1314

Botev ZI;L'Ecuyer P;Tuffin B, 2013, 'Markov chain importance sampling with applications to rare event probability estimation', Statistics and Computing, vol. 23, pp. 271 - 285, http://dx.doi.org/10.1007/s11222-011-9308-2

Botev ZI;Kroese DP;Rubinstein RY;L'Ecuyer P, 2013, 'The cross-entropy method for optimization', Handbook of Statistics, vol. 31, pp. 35 - 59, http://dx.doi.org/10.1016/B978-0-444-53859-8.00003-5

Botev ZI;L'Ecuyer P;Rubino G;Simard R;Tuffin B, 2013, 'Static network reliability estimation via generalized splitting', INFORMS Journal on Computing, vol. 25, pp. 56 - 71, http://dx.doi.org/10.1287/ijoc.1110.0493

Botev ZI;Kroese DP, 2012, 'Efficient Monte Carlo simulation via the generalized splitting method', Statistics and Computing, vol. 22, pp. 1 - 16, http://dx.doi.org/10.1007/s11222-010-9201-4

Botev ZI;Kroese DP, 2011, 'The Generalized Cross Entropy Method, with Applications to Probability Density Estimation', Methodology and Computing in Applied Probability, vol. 13, pp. 1 - 27, http://dx.doi.org/10.1007/s11009-009-9133-7

Botev ZI;Grotowski JF;Kroese DP, 2010, 'Kernel density estimation via diffusion', Annals of Statistics, vol. 38, pp. 2916 - 2957, http://dx.doi.org/10.1214/10-AOS799

Botev ZI;Kroese DP, 2008, 'Non-asymptotic bandwidth selection for density estimation of discrete data', Methodology and Computing in Applied Probability, vol. 10, pp. 435 - 451, http://dx.doi.org/10.1007/s11009-007-9057-z

Botev ZI;Kroese DP, 2008, 'An efficient algorithm for rare-event probability estimation, combinatorial optimization, and counting', Methodology and Computing in Applied Probability, vol. 10, pp. 471 - 505, http://dx.doi.org/10.1007/s11009-008-9073-7

Botev ZI;Kroese DP;Taimre T, 2007, 'Generalized Cross-entropy Methods with Applications to Rare-event Simulation and Optimization', Simulation, vol. 83, pp. 785 - 806, http://dx.doi.org/10.1177/0037549707087067

Conference Papers

Botev Z;L'Ecuyer P, 2017, 'Simulation from the normal distribution truncated to an interval in the tail', in ValueTools 2016 - 10th EAI International Conference on Performance Evaluation Methodologies and Tools, pp. 23 - 29, http://dx.doi.org/10.4108/eai.25-10-2016.2266879

Botev ZI;Ridder A, 2017, 'An M-Estimator for rare-event probability estimation', in Proceedings - Winter Simulation Conference, pp. 359 - 369, http://dx.doi.org/10.1109/WSC.2016.7822103

Botev ZI;Mandjes M;Ridder A, 2016, 'Tail distribution of the maximum of correlated Gaussian random variables', in Proceedings - Winter Simulation Conference, pp. 633 - 642, http://dx.doi.org/10.1109/WSC.2015.7408202

Botev ZI;L'Ecuyer P, 2016, 'Efficient probability estimation and simulation of the truncated multivariate student-t distribution', in Proceedings - Winter Simulation Conference, pp. 380 - 391, http://dx.doi.org/10.1109/WSC.2015.7408180

Botev ZI;Vaisman S;Rubinstein RY;L'Ecuyer P, 2015, 'Reliability of stochastic flow networks with continuous link capacities', in Proceedings - Winter Simulation Conference, pp. 543 - 552, http://dx.doi.org/10.1109/WSC.2014.7019919

Botev Z;L’Ecuyer P;Tuffin B, 2014, 'Modeling and Estimating Small Unreliabilities for Static Networks with Dependent Components', in Caruge D;Calvin C;Diop CM;Malvagi F;Trama J-C (eds.), SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo, SNA + MC2013 - Joint International Conference on Supecomputing in Nuclear Applications + Montel Carlo, Paris, France, pp. Article 03306, presented at SNA + MC2013 - Joint International Conference on Supecomputing in Nuclear Applications + Montel Carlo, Paris, France, 27 - 31 October 2013, http://dx.doi.org/10.1051/snamc/201403306

Botev ZI;L'Ecuyer P;Tuffin B, 2012, 'Dependent failures in highly reliable static networks', in Proceedings - Winter Simulation Conference, http://dx.doi.org/10.1109/WSC.2012.6465033

Botev ZI;L'Ecuyer P;Tuffin B, 2011, 'An importance sampling method based on a one-step look-ahead density from a Markov chain', in Proceedings - Winter Simulation Conference, pp. 528 - 539, http://dx.doi.org/10.1109/WSC.2011.6147782

Botev Z;Kroese D;Taimre T, 2006, 'Generalized cross-entropy methods', in Proceedings of RESIM, RESIM, Bamberg, Germany, pp. 1 - 30, presented at RESIM, Bamberg, Germany, 01 January 2006

Botev Z;Kroese DP, 2004, 'Global likelihood optimization via the cross-entropy method with an application to mixture models', in Proceedings - Winter Simulation Conference, pp. 529 - 535


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