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Expectation–maximization algorithm
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761	Biases in SPSS 12.0 Missing Value Analysis Paul T. vON HIPPEL In addition to SPSS Base software, SPSS Inc. sells a number of add-on packages, including a package called Missing Value Analysis (MVA). In version 12.0, MVA Add to Reading List Source URL: www.utexas.edu Language: English - Date: 2010-09-24 16:30:36 Estimation theory Econometrics Imputation Covariance and correlation Listwise deletion SPSS Variance Expectation–maximization algorithm Multivariate normal distribution Statistics Data analysis Missing data
762	Distributed Inference for Latent Dirichlet Allocation David Newman, Arthur Asuncion, Padhraic Smyth, Max Welling Department of Computer Science University of California, Irvine newman,asuncion,smyth,welling @ics.uci.ed Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-10-31 18:54:19 Latent Dirichlet allocation Linear discriminant analysis Machine learning Parallel computing Algorithm Gibbs sampling Mixture model Speedup Expectation–maximization algorithm Statistics Statistical natural language processing Statistical classification
763	Mixture Models and the EM Algorithm Christopher M. Bishop Microsoft Research, Cambridge 1 Add to Reading List Source URL: www.cs.ubbcluj.ro Language: English - Date: 2007-03-15 04:17:24 Statistical models Expectation propagation Bayesian inference Mixture model Expectation–maximization algorithm TrueSkill Statistics Bayesian statistics Machine learning
764	Package ‘arulesNBMiner’ July 30, 2014 Version[removed]Date[removed]Title Mining NB-Frequent Itemsets and NB-Precise Rules Author Michael Hahsler Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-30 12:25:26 Data management Estimation theory Expectation–maximization algorithm Statistics Data mining Association rule learning
765	Modeling Distributions of Reads from Leukemic Cells DNA through Mixture of Poisson Distributions ´ Flores Castillo ([removed]), Marek Kimmel ([removed]) Nicolas Department of Statistics, Rice University Add to Reading List Source URL: srcos2014.blogs.rice.edu Language: English - Date: 2014-07-30 15:44:37 Probability distribution Expectation–maximization algorithm Statistics Mathematical analysis Poisson distribution
766	Discussion of Particle Markov chain Monte Carlo methods by Andrieu et al. Anindya Bhadra, Department of Statistics, University of Michigan, Ann Arbor, MI[removed]USA The authors present an elegant theory for novel methodo Add to Reading List Source URL: www.stat.purdue.edu Language: English - Date: 2013-03-19 13:46:14 Statistical theory Statistical inference Likelihood function Maximum likelihood Iterated filtering Bayesian inference Expectation–maximization algorithm Statistics Estimation theory Bayesian statistics
767	Deep Mixtures of Factor Analysers Yichuan Tang [removed] Ruslan Salakhutdinov [removed] Add to Reading List Source URL: icml.cc Language: English - Date: 2012-06-07 13:19:54 Machine learning Data analysis Multivariate statistics Expectation–maximization algorithm Mixture model Principal component analysis Maximum likelihood Independent component analysis Supervised learning Statistics Statistical models Estimation theory
768	N EWS AND N OTES 186 Changes on CRAN[removed]to[removed] Add to Reading List Source URL: journal.r-project.org Language: English - Date: 2014-07-29 04:20:02 Econometrics Estimation theory Research methods Linear regression Meta-analysis Optimal design Multivariate analysis Expectation–maximization algorithm Mixture model Statistics Statistical methods Regression analysis
769	A New Approach of Genetic-based EM Algorithm for Mixture Models Sachith Abeysundara, Byungtae Seo (Department of Mathematics & Statistics) Abstract Simulation Results Add to Reading List Source URL: srcos2014.blogs.rice.edu Language: English - Date: 2014-07-29 16:34:29 Statistical models Expectation–maximization algorithm Missing data Bayesian statistics Mixture model Genetic algorithm Maximum likelihood Mixture distribution Algorithm Statistics Estimation theory Machine learning
770	Manifold Relevance Determination Andreas C. Damianou A NDREAS .DAMIANOU @ SHEFFIELD . AC . UK Dept. of Computer Science & Sheffield Institute for Translational Neuroscience, University of Sheffield, UK Carl Henrik Ek KTH Add to Reading List Source URL: icml.cc Language: English - Date: 2012-06-07 13:19:52 Multivariate statistics Latent variable Psychometrics Mutual information Principal component analysis Kriging Expectation–maximization algorithm Variational Bayesian methods Statistics Statistical models Bayesian networks

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