Literatura académica sobre el tema "Monte Carlo method"
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Artículos de revistas sobre el tema "Monte Carlo method"
Caflisch, Russel E. "Monte Carlo and quasi-Monte Carlo methods". Acta Numerica 7 (enero de 1998): 1–49. http://dx.doi.org/10.1017/s0962492900002804.
Texto completoMakarova, K. V., A. G. Makarov, M. A. Padalko, V. S. Strongin y K. V. Nefedev. "Multispin Monte Carlo Method". Dal'nevostochnyi Matematicheskii Zhurnal 20, n.º 2 (25 de noviembre de 2020): 212–20. http://dx.doi.org/10.47910/femj202020.
Texto completoRajabalinejad, M. "Bayesian Monte Carlo method". Reliability Engineering & System Safety 95, n.º 10 (octubre de 2010): 1050–60. http://dx.doi.org/10.1016/j.ress.2010.04.014.
Texto completoThe Lam, Nguyen. "QUANTUM DIFFUSION MONTE CARLO METHOD FOR LOW-DIMENTIONAL SYSTEMS". Journal of Science, Natural Science 60, n.º 7 (2015): 81–87. http://dx.doi.org/10.18173/2354-1059.2015-0036.
Texto completoSiyamah, Imroatus, Endah RM Putri y Chairul Imron. "Cat bond valuation using Monte Carlo and quasi Monte Carlo method". Journal of Physics: Conference Series 1821, n.º 1 (1 de marzo de 2021): 012053. http://dx.doi.org/10.1088/1742-6596/1821/1/012053.
Texto completoKandidov, V. P. "Monte Carlo method in nonlinear statistical optics". Uspekhi Fizicheskih Nauk 166, n.º 12 (1996): 1309. http://dx.doi.org/10.3367/ufnr.0166.199612c.1309.
Texto completoRashki, Mohsen. "The soft Monte Carlo method". Applied Mathematical Modelling 94 (junio de 2021): 558–75. http://dx.doi.org/10.1016/j.apm.2021.01.022.
Texto completoAboughantous, Charles H. "A Contributorn Monte Carlo Method". Nuclear Science and Engineering 118, n.º 3 (noviembre de 1994): 160–77. http://dx.doi.org/10.13182/nse94-a19382.
Texto completoBruce, A. D., A. N. Jackson, G. J. Ackland y N. B. Wilding. "Lattice-switch Monte Carlo method". Physical Review E 61, n.º 1 (1 de enero de 2000): 906–19. http://dx.doi.org/10.1103/physreve.61.906.
Texto completoGubernatis, Jim y Naomichi Hatano. "The multicanonical Monte Carlo method". Computing in Science & Engineering 2, n.º 2 (marzo de 2000): 95–102. http://dx.doi.org/10.1109/mcise.2000.5427643.
Texto completoTesis sobre el tema "Monte Carlo method"
Janzon, Krister. "Monte Carlo Path Simulation and the Multilevel Monte Carlo Method". Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-151975.
Texto completoLacasse, Martin Daniel. "New dynamical Monte Carlo renormalization group method". Thesis, McGill University, 1990. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=60062.
Texto completoZhang, Yichuan. "Scalable geometric Markov chain Monte Carlo". Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20978.
Texto completoVeld, Pieter Jacob in 't. "Monte Carlo studies of liquid structure /". Digital version:, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p9992826.
Texto completoHazelton, Martin Luke. "Method of density estimation with application to Monte Carlo methods". Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334850.
Texto completoLefebvre, Geneviève 1978. "Practical issues in modern Monte Carlo integration". Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103209.
Texto completoUsing an identity arising in path sampling, we then derive general expressions for the Kullback-Leibler (KL) and Jeffrey (J) divergences between two distributions with common support but from possibly different parametric families. These expressions naturally stem from path sampling when the popular geometric path is used to link the extreme densities. Expressions for the KL and J-divergences are also given for any two intermediate densities lying on the path. Estimates for the KL divergence (up to a constant) and for the J-divergence, between a posterior distribution and a selected importance density, can be obtained directly, prior to path sampling implementation. The J-divergence is shown to be helpful for choosing importance densities that minimize the error of the path sampling estimates.
Finally we present the results of a simulation study devised to investigate whether improvement in performance can be achieved by using the KL and J-divergences to select sequences of distributions in parallel (population-based) simulations, such as in the Sequential Monte Carlo Sampling and the Annealed Importance Sampling algorithms. We compare these choices of sequences to more conventional choices in the context of a mixture example. Unexpected results are obtained, and those for the KL and J-divergences are mixed. More fundamentally, we uncover the need to select the sequence of tempered distributions in accordance with the resampling scheme.
Lee, Ming Ripman y 李明. "Monte Carlo simulation for confined electrolytes". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31240513.
Texto completoLee, Ming Ripman. "Monte Carlo simulation for confined electrolytes /". Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22055009.
Texto completoYam, Chiu Yu. "Quasi-Monte Carlo methods for bootstrap". HKBU Institutional Repository, 2000. http://repository.hkbu.edu.hk/etd_ra/272.
Texto completoWong, Ping-yung. "Molecular clusters on surfaces : a Monte Carlo study /". Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20566694.
Texto completoLibros sobre el tema "Monte Carlo method"
Lemieux, Christiane. Monte carlo and quasi-monte carlo sampling. New York: Springer, 2009.
Buscar texto completoKalos, Malvin H. Monte Carlo methods. New York: J. Wiley & Sons, 1986.
Buscar texto completoDunn, William L. Exploring Monte Carlo methods. Amsterdam: Elsevier/Academic Press, 2012.
Buscar texto completo1957-, Madras Neal Noah, Fields Institute for Research in Mathematical Sciences. y Workshop on Monte Carlo Methods (1998 : Toronto, Ont.), eds. Monte Carlo methods. Providence, RI: American Mathematical Society, 2000.
Buscar texto completoI, Schueller G., ed. Monte Carlo simulation. Lisse: A.A. Balkema, 2001.
Buscar texto completoFox, Bennett L. Strategies for quasi-Monte Carlo. Boston: Kluwer Academic, 1999.
Buscar texto completoPierre, L' Ecuyer y Owen Art B, eds. Monte Carlo and quasi-Monte Carlo methods 2008. Heidelberg: Springer, 2009.
Buscar texto completoCasella, George y Christian P. Robert. Monte Carlo Statistical Methods. 2a ed. New York, USA: Springer, 2004.
Buscar texto completoKroese, Dirk P., Thomas Taimre, Zdravko I. Botev y Rueven Y. Rubinstein. Simulation and the Monte Carlo Method. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470285312.
Texto completoRubinstein, Reuven Y. y Dirk P. Kroese. Simulation and the Monte Carlo Method. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781118631980.
Texto completoCapítulos de libros sobre el tema "Monte Carlo method"
Liou, William W. "Monte Carlo Method". En Encyclopedia of Microfluidics and Nanofluidics, 2315–19. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-5491-5_1059.
Texto completoLiou, William W. "Monte Carlo Method". En Encyclopedia of Microfluidics and Nanofluidics, 1–5. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-3-642-27758-0_1059-3.
Texto completoWeik, Martin H. "Monte Carlo method". En Computer Science and Communications Dictionary, 1045. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11803.
Texto completoMosegaard, Klaus. "Monte Carlo Method". En Encyclopedia of Mathematical Geosciences, 1–7. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-26050-7_431-2.
Texto completoMosegaard, Klaus. "Monte Carlo Method". En Encyclopedia of Mathematical Geosciences, 1–7. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_431-1.
Texto completoMosegaard, Klaus. "Monte Carlo Method". En Encyclopedia of Mathematical Geosciences, 890–96. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_431.
Texto completoChoe, Geon Ho. "The Monte Carlo Method for Option Pricing Monte Carlo method". En Universitext, 501–17. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25589-7_28.
Texto completoBuckley, James J. y Leonard J. Jowers. "Fuzzy Monte Carlo Method". En Monte Carlo Methods in Fuzzy Optimization, 57–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-76290-4_6.
Texto completoRollett, Anthony D. y Priya Manohar. "The Monte Carlo Method". En Continuum Scale Simulation of Engineering Materials, 77–114. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2005. http://dx.doi.org/10.1002/3527603786.ch4.
Texto completoTildesley, D. J. "The Monte Carlo Method". En Computer Simulation in Chemical Physics, 1–22. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1679-4_1.
Texto completoActas de conferencias sobre el tema "Monte Carlo method"
Wilding, Nigel B. "Phase Switch Monte Carlo". En THE MONTE CARLO METHOD IN THE PHYSICAL SCIENCES: Celebrating the 50th Anniversary of the Metropolis Algorithm. AIP, 2003. http://dx.doi.org/10.1063/1.1632147.
Texto completoFrenkel, D. "Biased Monte Carlo Methods". En THE MONTE CARLO METHOD IN THE PHYSICAL SCIENCES: Celebrating the 50th Anniversary of the Metropolis Algorithm. AIP, 2003. http://dx.doi.org/10.1063/1.1632121.
Texto completoBilgin, Muhammed y Tolga Ensari. "Robot localization with Monte Carlo method". En 2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT). IEEE, 2017. http://dx.doi.org/10.1109/ebbt.2017.7956755.
Texto completoLing*, Yue, Huazhong Wang y Shaoyong Liu. "Monte Carlo background velocity inversion method". En Beijing 2014 International Geophysical Conference & Exposition, Beijing, China, 21-24 April 2014. Society of Exploration Geophysicists and Chinese Petroleum Society, 2014. http://dx.doi.org/10.1190/igcbeijing2014-188.
Texto completoPapp, Zsolt, Janos Kornis y Balazs Gombkoto. "Monte Carlo method in digital holography". En Speckle Metrology 2003. SPIE, 2003. http://dx.doi.org/10.1117/12.516573.
Texto completoGonzalez-Jorge, H., J. L. Valencia, V. Alvarez, F. Rodriguez y F. J. Yebra. "Monte-Carlo method in AFM calibration". En 2009 Spanish Conference on Electron Devices (CDE). IEEE, 2009. http://dx.doi.org/10.1109/sced.2009.4800526.
Texto completoStoffova, Veronika y R. Horváth. "MONTE CARLO METHOD IN EDUCATIONAL PRACTICE". En 13th annual International Conference of Education, Research and Innovation. IATED, 2020. http://dx.doi.org/10.21125/iceri.2020.1532.
Texto completoZhu, Juan, Shuai Wang, Da-wei Wang, Yan-ying Liu y Yan-jie Wang. "Monte Carlo Tracking Method with Threshold Constraint". En 2009 2nd International Congress on Image and Signal Processing (CISP). IEEE, 2009. http://dx.doi.org/10.1109/cisp.2009.5301685.
Texto completoChen, Nanguang. "Controlled Monte Carlo Method for Reflection Geometry". En Biomedical Topical Meeting. Washington, D.C.: OSA, 2006. http://dx.doi.org/10.1364/bio.2006.me9.
Texto completoDIMOV, IVAN y ANETA KARAIVANOVA. "A POWER METHOD WITH MONTE CARLO ITERATIONS". En Proceedings of the Fourth International Conference. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814291071_0022.
Texto completoInformes sobre el tema "Monte Carlo method"
Hill, James Lloyd. Introduction to the Monte Carlo Method. Office of Scientific and Technical Information (OSTI), junio de 2020. http://dx.doi.org/10.2172/1634920.
Texto completoBlomquist, R. N. y E. M. Gelbard. Alternative implementations of the Monte Carlo power method. Office of Scientific and Technical Information (OSTI), marzo de 2002. http://dx.doi.org/10.2172/793906.
Texto completoSvatos, M. The macro response Monte Carlo method for electron transport. Office of Scientific and Technical Information (OSTI), septiembre de 1998. http://dx.doi.org/10.2172/3847.
Texto completoFishman, George S. Sensitivity Analysis Using the Monte Carlo Acceptance-Rejection Method. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 1988. http://dx.doi.org/10.21236/ada201261.
Texto completoCarlin, Bradley P. y Alan E. Gelfand. An Iterative Monte Carlo Method for Nonconjugate Bayesian Analysis. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 1992. http://dx.doi.org/10.21236/ada255991.
Texto completoTaro Ueki. A Multivariate Time Series Method for Monte Carlo Reactor Analysis. Office of Scientific and Technical Information (OSTI), agosto de 2008. http://dx.doi.org/10.2172/935876.
Texto completoRichie, David A., James A. Ross, Song J. Park y Dale R. Shires. A Monte Carlo Method for Multi-Objective Correlated Geometric Optimization. Fort Belvoir, VA: Defense Technical Information Center, mayo de 2014. http://dx.doi.org/10.21236/ada603830.
Texto completoActon, Scott T. y Bing Li. A Sequential Monte Carlo Method for Real-time Tracking of Multiple Targets. Fort Belvoir, VA: Defense Technical Information Center, mayo de 2010. http://dx.doi.org/10.21236/ada532576.
Texto completoBoyd, Iain D. A Threshold Line Dissociation Model for the Direct Simulation Monte Carlo Method,. Fort Belvoir, VA: Defense Technical Information Center, mayo de 1996. http://dx.doi.org/10.21236/ada324950.
Texto completoPolitis, Dimitris N., Raffaella Giacomini y Halbert White. A warp-speed method for conducting Monte Carlo experiments involving bootstrap estimators. Cemmap, mayo de 2012. http://dx.doi.org/10.1920/wp.cem.2012.1112.
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