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Gibbs sampling
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211	Package ‘rjags’ July 2, 2014 Version 3-13 Date[removed]Title Bayesian graphical models using MCMC Depends R (>= 2.14.0), coda (>= 0.13) Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-10-27 13:35:05 Graphical models Deviance information criterion Cross-platform software Gibbs sampling Artificial neuron Functional Markov chain JavaScript Deviance Statistics Bayesian statistics Markov models
212	Combinatorial Markov Random Fields Ron Bekkerman1 , Mehran Sahami2 , and Erik Learned-Miller1 1 Department of Computer Science, University of Massachusetts, Amherst MA 01002, {ronb\|elm}@cs.umass.edu, Add to Reading List Source URL: vis-www.cs.umass.edu Language: English - Date: 2008-01-02 15:36:23 Cluster analysis Expectation–maximization algorithm Mutual information Unsupervised learning Statistical classification Semi-supervised learning Gibbs sampling Consensus clustering Adjusted mutual information Statistics Machine learning Computational statistics
213	Package ‘hSDM’ July 2, 2014 Type Package Title hierarchical Bayesian species distribution models Version 1.4 Date[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:06:20 Hierarchical Bayes model Gibbs sampling Prior probability Regression analysis Ecology Estimation theory Statistics Bayesian statistics Probability and statistics
214	New URL: http://www.R-project.org/conferences/DSC[removed]Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC[removed]March 20–22, Vienna, Austria ISSN 1609-395X Add to Reading List Source URL: www.r-project.org Language: English - Date: 2014-02-10 04:25:54 Markov models Just another Gibbs sampler Graphical models Monte Carlo software WinBUGS Markov chain Monte Carlo Gibbs sampling Bayesian network Bayesian inference Statistics Bayesian statistics Statistical models
215	An Introduction to iBUGS Yihui Xie∗ and Jiebiao Wang† December 10, 2013 iBUGS is an R package which aims to make it easier to call WinBUGS1 , OpenBUGS2 and JAGS3 in R, under the operating systems of Windows and Linux Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:09:42 Computing Just another Gibbs sampler OpenBUGS WinBUGS RGtk2 R Debian Environment variable Gibbs sampling Software Statistics Monte Carlo software
216	Teaching Bayes to Graduate Students in Political Science, Sociology, Public Health, Education, Economics, . . . Andrew G ELMAN 1. INTRODUCTION I was trying to draw Bert and Ernie the other day, and it was really difficul Add to Reading List Source URL: www.stat.columbia.edu Language: English - Date: 2008-06-26 16:52:25 Statistical theory Estimation theory Parametric statistics Linear regression Andrew Gelman Statistical inference Simple linear regression Bayesian inference Gibbs sampling Statistics Regression analysis Econometrics
217	Bayesian Nonparametric Learning with semi-Markovian Dynamics by Matthew J Johnson B.S. in Electrical Engineering and Computer Sciences Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2012-02-01 13:36:21 Hidden Markov models Bayesian statistics Markov models Hidden semi-Markov model Dirichlet process Gibbs sampling Bayesian inference Mixture model Non-parametric statistics Statistics Stochastic processes Statistical inference
218	Online Polylingual Topic Models for Fast Document Translation Detection Kriste Krstovski School of Computer Science University of Massachusetts Amherst Amherst, MA, [removed]removed] Add to Reading List Source URL: aclweb.org Language: English - Date: 2013-07-25 09:32:19 Latent Dirichlet allocation Topic model Kullback–Leibler divergence Gibbs sampling Hellinger distance Variational Bayesian methods Probabilistic latent semantic analysis Expectation–maximization algorithm Information retrieval Statistics Statistical natural language processing Dynamic topic model
219	T O APPEAR IN N EURAL I NFORMATION P ROCESSING S YSTEMS[removed]Efficient Multiscale Sampling from Products of Gaussian Mixtures Alexander T. Ihler, Erik B. Sudderth, William T. Freeman, and Alan S. Willsky Department of E Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2012-02-01 13:34:22 Computational statistics Estimation theory Gaussian function Gibbs sampling Normal distribution Expectation–maximization algorithm Kullback–Leibler divergence Multivariate kernel density estimation Importance sampling Statistics Monte Carlo methods Non-parametric statistics
220	The Ising model and Markov chain Monte Carlo Ramesh Sridharan∗ These notes give a short description of the Ising model for images and an introduction to Metropolis-Hastings and Gibbs Markov Chain Monte Carlo (MCMC). Th Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2014-01-26 15:07:54 Computational statistics Markov chain Monte Carlo Markov models Statistical mechanics Metropolis–Hastings algorithm Gibbs sampling Markov random field Ising model Markov chain Statistics Probability and statistics Monte Carlo methods

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