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Mixture theory
Results: 438

#	Item
261	Forensic DNA Mixture Interpretation Statistical Approaches for DNA Mixtures MAFS Workshop Add to Reading List Source URL: www.cstl.nist.gov Language: English - Date: 2012-09-28 09:23:14 Probability interpretations Bayesian statistics Frequentist inference Probability theory Probability Bayesian probability Likelihood principle Bayes factor Statistics Statistical inference Philosophy of science
262	Engineering Tripos Part IIB FOURTH YEAR Module 4F10: STATISTICAL PATTERN RECOGNITION Examples Paper 1 Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2013-11-08 06:57:05 Statistical theory Maximum likelihood Normal distribution Variance Expectation–maximization algorithm Mixture model Covariance matrix Mixture distribution Statistics Estimation theory Data analysis
263	Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models Jimena Davis1, John Wambaugh1, Ramon I. Garcia2, R. Woodrow Setzer1 research d ev el opme nt Add to Reading List Source URL: epa.gov Language: English - Date: 2012-05-07 10:14:12 Physiologically based pharmacokinetic modelling Hierarchical Bayes model Estimation theory Prior probability Confidence interval Parameter Point estimation Hyperparameter Mixture model Statistics Bayesian statistics Statistical inference
264	Journal of Machine Learning Research[removed]1347 Submitted 6/12; Published 5/13 Stochastic Variational Inference Matthew D. Hoffman Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2013-06-14 05:31:44 Estimation theory Econometrics Statistical models Expectation–maximization algorithm Mixture model Markov chain Linear regression Latent Dirichlet allocation Regression analysis Statistics Bayesian statistics Markov models
265	Continuous Time Dynamic Topic Models Chong Wang Computer Science Dept. Princeton University Princeton, NJ 08540 Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2010-08-18 22:20:53 Statistical models Dynamic topic model Markov models Control theory Variational Bayesian methods Latent Dirichlet allocation Mixture model Topic model Probabilistic latent semantic analysis Statistics Statistical natural language processing Bayesian statistics
266	Package ‘disclapmix’ July 2, 2014 Type Package Title Discrete Laplace mixture inference using the EM algorithm Version 1.5 Date[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 11:38:12 Genetic genealogy Estimation theory Haplotype Probability theory Expectation–maximization algorithm Marginal likelihood Laplace distribution Algorithm Probability distribution Statistics Mathematics Applied mathematics
267	Journal of Machine Learning Research[removed]2410 Submitted 10/09; Revised 12/10; Published 8/10 Distance Dependent Chinese Restaurant Processes David M. Blei Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2013-02-16 21:04:48 Machine learning Probability theory Dirichlet process Chinese restaurant process Mixture model Cluster analysis Mixture Exchangeable random variables Statistics Stochastic processes Statistical models
268	5. Mixtures and Products of Experts University of Cambridge Engineering Part IIB Module 4F10: Statistical Pattern Processing Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2013-11-13 04:10:48 Maximum likelihood Likelihood function Multivariate normal distribution Mixture model Normal distribution Statistics Estimation theory Expectation–maximization algorithm
269	Model-Based Approaches to Handling Uncertainty M.J.F. Gales Abstract A powerful approach for handling uncertainty in observations is to modify the statistical model of the data to appropriately reflect this uncertainty. Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2010-09-03 04:10:35 Statistical inference Markov models Statistical models Multivariate normal distribution Speech recognition Hidden Markov model Additive white Gaussian noise Mixture model Linear regression Statistics Estimation theory Regression analysis
270	Learning Stochastic Feedforward Neural Networks Yichuan Tang Department of Computer Science University of Toronto Toronto, Ontario, Canada. Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-11-19 21:06:13 Machine learning Estimation theory Statistical theory Expectation–maximization algorithm Bayesian network Gibbs sampling Perceptron Kullback–Leibler divergence Mixture model Statistics Statistical models Neural networks

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