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Multivariate normal distribution
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271	g03 – Multivariate Methods Introduction – g03 NAG Library Chapter Introduction g03 – Multivariate Methods Add to Reading List Source URL: www.nag.com Language: English - Date: 2014-01-21 11:26:02 Covariance and correlation Market research Psychometrics Principal component analysis Multivariate normal distribution Linear discriminant analysis Factor analysis Hierarchical clustering Canonical correlation Statistics Multivariate statistics Data analysis
272	ROM SIMULATION Exact Moment Simulation using Random Orthogonal Matrices Bachelier Finance Society Meeting Toronto 2010 Add to Reading List Source URL: www.fields.utoronto.ca Language: English - Date: 2010-06-18 08:47:58 Probability theory Data analysis Multivariate normal distribution Normal distribution Skewness Kurtosis Matrix ICMA Centre Orthogonal matrix Statistics Mathematical analysis Matrices
273	CORRELATION UNDER STRESS IN NORMAL VARIANCE MIXTURE MODELS Natalie Packham Joint work with Michael Kalkbrener Add to Reading List Source URL: www.fields.utoronto.ca Language: English - Date: 2010-06-20 11:42:17 Covariance and correlation Mathematical finance Normal distribution Stress testing Correlation and dependence Multivariate normal distribution Mixture model Mixture distribution Statistics Probability and statistics Probability
274	Genetic Epidemiology 8:[removed]Efficient Computation of Patterned Covariance Matrix Mixed Models in Quantitative Segregation Analysis Nicholas Schork Add to Reading List Source URL: deepblue.lib.umich.edu Language: English - Date: 2006-05-18 06:58:52 Abstract algebra Linear algebra Estimation theory Data analysis Covariance and correlation Covariance matrix Mixed model Euclidean vector Multivariate normal distribution Statistics Algebra Mathematics
275	Learning Graphs with a Few Hubs Rashish Tandon, Pradeep Ravikumar Department of Computer Science The University of Texas at Austin, USA Add to Reading List Source URL: jmlr.org Language: English - Date: 2014-02-16 19:30:21 Maximum likelihood Connectivity Multivariate normal distribution Estimator Sufficient statistic Maximum spacing estimation Poisson distribution Statistics Estimation theory Statistical theory
276	High-dimensional covariance estimation by minimizing 1-penalized log-determinant divergence Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2011-05-03 19:18:22 Data analysis Matrices Multivariate normal distribution Normal distribution Fisher information Maximum likelihood Covariance matrix Covariance Matrix Statistics Estimation theory Covariance and correlation
277	Elementary Estimators for Sparse Covariance Matrices and other Structured Moments Eunho Yang Department of Computer Science, The University of Texas, Austin, TX 78712, USA EUNHO @ CS . UTEXAS . EDU Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2014-05-12 15:27:32 Regression analysis Covariance and correlation Statistical theory Multivariate normal distribution Covariance Maximum likelihood Normal distribution Linear regression Variance Statistics Estimation theory Data analysis
278	High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods Christopher C. Johnson CS, UT Austin [removed] Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2012-04-26 08:56:37 Fisher information Multivariate normal distribution Maximum likelihood Expectation–maximization algorithm Statistics Estimation theory Feature selection
279	ECAI 2014 T. Schaub et al. (Eds.) © 2014 The Authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial Licen Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2014-08-03 02:46:45 Multivariate statistics Singular value decomposition Linear algebra Numerical linear algebra Principal component analysis Conjugate prior Variational Bayesian methods Normal distribution Multivariate normal distribution Statistics Algebra Bayesian statistics
280	Topographic Factor Analysis: A Bayesian Model for Inferring Brain Networks from Neural Data Jeremy R. Manning1,2, Rajesh Ranganath2, Kenneth A. Norman1,3, David M. Blei2 1 Princeton Neuroscience Institute, Princeton Uni Add to Reading List Source URL: compmem.princeton.edu Language: English* - Date: 2014-05-15 17:35:54 Magnetic resonance imaging Neuroimaging Statistical models Functional magnetic resonance imaging Normal distribution Principal component analysis Kullback–Leibler divergence Independent component analysis Statistics Data analysis Multivariate statistics

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