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Monte Carlo methods
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121	reprinted from Monte Carlo and Quasi-Monte Carlo Methods 1998, H. Niederreiter and J. Spanier, eds., Springer-Verlag, 2000, ppA LeVeque-type lower bound for discrepancy Francis Edward Su Department of Mathemat Add to Reading List Source URL: www.math.hmc.edu Language: English - Date: 2000-06-02 09:35:28
122	Header for SPIE use Evaluation of scatter correction methods using Monte Carlo simulation in non uniform media Georges El Fakhri, Philippe Maksud and André Aurengo U494 INSERM, CHU Pitié Salpêtrière, Paris, France Add to Reading List Source URL: nmmiweb.mgh.harvard.edu Language: English - Date: 2013-03-01 11:14:57
123	Convergence rates of Markov chain Monte Carlo methods by: David Clement* 1. Introduction The following paper deals with the convergence rates of Markov Chain Monte Carlo (MCMC) algorithms. Section 2 provides a short revi Add to Reading List Source URL: probability.ca Language: English - Date: 2003-08-28 16:54:24
124	Monte Carlo Methods for the Linearized Poisson-Boltzmann Equation Chi-Ok Hwang, Michael Mascagni and Nikolai A. Simonov a,b,c a Computational Electronics Center, Inha University, 253 Yonghyun-Dong Add to Reading List Source URL: www.cs.fsu.edu Language: English - Date: 2003-10-13 13:53:54
125	Label Switch in Mixture Model and Relabeling Algorithm Project for Reading Course Prepared by: Fanfu Xie, ZhengFei Chen Label Switch in Mixture Model and Relabeling Algorithm Add to Reading List Source URL: probability.ca Language: English - Date: 2009-08-30 09:25:51 Estimation theory Computational statistics Monte Carlo methods Bayesian statistics Mixture model Markov chain Monte Carlo Markov chain Mixture distribution Gibbs sampling Statistics Probability and statistics Markov models
126	Simulating Biochemical Reaction Networks using Lattice Microbes: A Workflow August 3rd, 2012 Piyush Labhsetwar, Elijah Roberts and Zaida Luthey-Schulten Add to Reading List Source URL: www.scs.illinois.edu Language: English - Date: 2012-10-26 21:49:49 Chemical kinetics Probability and statistics Monte Carlo methods Computational chemistry Stochastic models Gillespie algorithm Stochastic simulation MATLAB Reaction rate Statistics Software Stochastic processes
127	Importance Sampling Estimates for Policies with Memory Christian R. Shelton MIT, AI Lab 545 Technology Square, NE43-741, Cambridge, MAUSA Abstract Add to Reading List Source URL: www.cs.ucr.edu Language: English - Date: 2003-05-27 20:51:52 Monte Carlo methods Computational statistics Importance sampling Variance reduction Pi Logarithm Hidden Markov model Reinforcement learning Markov models Mathematical analysis Mathematics
128	Scaling Limits for the Transient Phase of Local Metropolis-Hastings Algorithms by Ole F. Christensen* and Add to Reading List Source URL: probability.ca Language: English - Date: 2006-10-04 20:54:37 Stochastic processes Markov models Markov chain Monte Carlo Theoretical computer science Metropolis–Hastings algorithm Random walk Algorithm Normal distribution Convergence of random variables Statistics Probability and statistics Monte Carlo methods
129	A Hierarchical Bayes based approach to ensemble-variational data assimilation M Tsyrulnikov and A Rakitko Motivation Add to Reading List Source URL: srnwp.met.hu Language: English - Date: 2014-10-27 11:08:29 Data analysis Monte Carlo methods Covariance and correlation Ensemble Kalman filter Covariance matrix Covariance Data assimilation Normal distribution Importance sampling Statistics Estimation theory Bayesian statistics
130	Copyright Cambridge University PressOn-screen viewing permitted. Printing not permitted. http://www.cambridge.orgYou can buy this book for 30 pounds or $50. See http://www.inference.phy.cam.ac.uk/macka Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2004-09-18 13:29:32 Monte Carlo methods Markov chain Monte Carlo Statistical mechanics Bayesian inference Statistical inference Normal distribution Metropolis–Hastings algorithm Marginal likelihood Variational Bayesian methods Statistics Probability and statistics Bayesian statistics