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Maximum likelihood estimation
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#	Item
771	6.867 Machine learning, lecture 17 (Jaakkola) 1 Lecture topics: • Mixture models and clustering, k-means Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 Estimation theory Cluster analysis Data mining Expectation–maximization algorithm K-means clustering Information bottleneck method Hierarchical clustering Mixture model Maximum likelihood Statistics Multivariate statistics Machine learning
772	gllamm companion for Rabe-Hesketh, S. and Skrondal, AMultilevel and Longitudinal Modeling Using Stata (3rd Edition). Volume I: Continuous Responses. College Station, TX: Stata Press. Add to Reading List Source URL: www.gllamm.org Language: English - Date: 2012-03-21 01:42:13 Regression analysis Analysis of variance Statistical methods Heteroscedasticity Maximum likelihood Empirical Bayes method Variance Mixed model Normal distribution Statistics Estimation theory Econometrics
773	A prior predictive loss function for the evaluation of inequality constrained hypotheses Add to Reading List Source URL: rensvandeschoot.files.wordpress.com Language: English - Date: 2014-06-03 07:54:10 Econometrics Design of experiments Fisher information Information theory Loss function Score Maximum likelihood Estimation theory Statistics Statistical theory
774	Hierarchical Latent Dictionaries for Models of Brain Activation Alona Fyshe Machine Learning Carnegie Mellon University Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2013-09-06 21:39:41 Variational Bayesian methods Normal distribution Maximum likelihood Gaussian process Interpretation Principal component analysis Statistics Bayesian statistics Estimation theory
775	Improved growth estimates from integrated analysis of age-at-length and tag-recapture data for BET and YFT and their impact on stock assessment results Alexandre Aires-da-Silva, Mark Maunder, Kurt Schaefer and Dan Fuller Add to Reading List Source URL: www.iotc.org Language: English - Date: 2014-09-02 02:48:06 Statistical inference Signal processing Scombridae Maximum likelihood Tuna Fish Statistics Estimation theory
776	The Likelihood Ratio, Wald, and Lagrange Multiplier Tests: An Expository Note Author(s): A. Buse Reviewed work(s): Source: The American Statistician, Vol. 36, No. 3, Part 1 (Aug., 1982), pp[removed]Published by: America Add to Reading List Source URL: teach.business.uq.edu.au Language: English - Date: 2015-02-05 22:25:26 Statistical theory Econometrics Time series analysis Score test Wald test Likelihood-ratio test Maximum likelihood Fisher information Autoregressive conditional heteroskedasticity Statistics Statistical tests Estimation theory
777	Large Sample Properties of Generalized Method of Moments Estimators Author(s): Lars Peter Hansen Reviewed work(s): Source: Econometrica, Vol. 50, No. 4 (Jul., 1982), pp[removed]Published by: The Econometric Society St Add to Reading List Source URL: teach.business.uq.edu.au Language: English - Date: 2015-02-05 22:25:33 Econometrics Statistical inference Regression analysis Estimator Consistent estimator Asymptotic theory Generalized method of moments Efficient estimator Maximum likelihood Statistics Estimation theory Statistical theory
778	Theoretical background for WinBUGS code HMM.odc Estimation of infection and recovery rates for highly polymorphic parasites when detectability is imperfect, using hidden Markov models Tom Smith & Penelope Vounatsou Add to Reading List Source URL: www.swisstph.ch Language: English - Date: 2013-09-12 05:44:20 Markov processes Estimation theory Bioinformatics Markov chain Hidden Markov model Markov property Expectation–maximization algorithm Mixture model Maximum likelihood Statistics Markov models Probability and statistics
779	The University of Adelaide School of Economics Research Paper No[removed]July 2011 Add to Reading List Source URL: economics.adelaide.edu.au Language: English - Date: 2014-08-10 21:21:47 Markov models Statistical theory Options Normal distribution Markov chain Maximum likelihood Univariate Likelihood function Probability distribution Statistics Mathematical finance Estimation theory
780	1 Learning Graphical Model Parameters with Approximate Marginal Inference Justin Domke, NICTA & Australia National University Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2013-09-04 21:04:45 Expectation–maximization algorithm Maximum likelihood Bayes estimator Loss function Sufficient statistic Belief propagation Statistics Estimation theory Statistical theory

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