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Marginal likelihood
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21	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
22	Journal of Econometrics – 187 www.elsevier.com/locate/econbase Comparing dynamic equilibrium models to data: a Bayesian approach Add to Reading List Source URL: econ.duke.edu Language: English - Date: 2012-09-24 16:50:25 Bayesian inference Estimation theory Probability theory Bayes factor Kullback–Leibler divergence Maximum likelihood Prior probability Marginal likelihood Bayesian probability Statistics Bayesian statistics Statistical theory
23	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.inference.phy.cam.ac.uk Language: English - Date: 2005-05-21 12:28:11 Estimation theory Poisson processes Statistical theory Exponential distribution Bayesian inference Information theory Likelihood function Normalizing constant Marginal likelihood Statistics Bayesian statistics Probability theory
24	Title stata.com bayesmh evaluators — User-defined evaluators with bayesmh Description Stored results Add to Reading List Source URL: www.stata.com Language: English - Date: 2015-04-22 14:53:09 Estimation theory Econometrics Bayesian inference Bayesian linear regression Likelihood function Linear regression Marginal likelihood Prior probability Likelihood-ratio test Statistics Bayesian statistics Regression analysis
25	Unsupervised Learning∗ Zoubin Ghahramani† Gatsby Computational Neuroscience Unit University College London, UK http://www.gatsby.ucl.ac.uk/~zoubin Add to Reading List Source URL: www.inf.ed.ac.uk Language: English - Date: 2005-11-29 12:55:06 Statistical theory Machine learning Markov models Expectation–maximization algorithm Maximum likelihood Hidden Markov model Mixture model Kullback–Leibler divergence Marginal likelihood Statistics Estimation theory Bayesian statistics
26	Inferring the Number of Component Spectra in Multiplexed SERRS M. Zhong, M. Girolami, K. Faulds, & D.Graham * Inference Group, Department of Computing Science, University of Glasgow, http://www.dcs.gla.ac.uk/infere Add to Reading List Source URL: www.dcs.gla.ac.uk Language: English - Date: 2009-01-27 07:16:33 Bayesian statistics Bayesian information criterion Marginal likelihood Markov chain Spectrum Bayes factor Normal distribution Statistics Bayesian inference Model selection
27	Journal of Artificial Intelligence Research203 Submitted 11/12; publishedA Survey on Latent Tree Models and Applications Rapha¨ Add to Reading List Source URL: jair.org Language: English - Date: 2013-05-31 00:53:01 Latent variable Expectation–maximization algorithm Latent class model Bayesian network Graphical model Mixture model Marginal likelihood Statistics Statistical models Bayesian statistics
28	Latent GOLD 4.0 and IRT modeling Jeroen K. Vermunt & Jay Magidson February 23, 2006 Latent GOLD 4.0 can be used to obtain MML (Marginal Maximum Likelihood) estimates for a large variety of well-known IRT models, such as Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2006-09-05 12:23:44 Rasch model Latent variable model Logistic regression Level of measurement Regression analysis Statistics Statistical models Psychometrics
29	Expectation Maximization for Weakly Labeled Data Yuri Ivanov MIT Media Laboratory, 20 Ames St., E15-390, Cambridge, MA 02139, USA Add to Reading List Source URL: characters.media.mit.edu Language: English - Date: 2003-06-30 17:21:48 Maximum likelihood Kullback–Leibler divergence M-estimator Likelihood function Reinforcement learning Divergence Multi-armed bandit Marginal likelihood Extremum estimator Statistics Estimation theory Expectation–maximization algorithm
30	Bayesian Model Averaging Using the k-best Bayesian Network Structures Jin Tian, Ru He and Lavanya Ram Department of Computer Science Iowa State University Ames, IA 50011 Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2010-06-14 14:21:41 Bayesian inference Markov chain Graphical model Marginal likelihood Estimation theory Prior probability Particle filter Bayesian inference in phylogeny Statistics Bayesian statistics Bayesian network

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