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Covariance matrix
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#	Item
261	Principal component and reconstructed radiance based assimilation techniques Marco Matricardi, Tony McNally and Niels Bormann ECMWF Shinfield Park, Reading, UK Add to Reading List Source URL: www.ecmwf.int Language: English - Date: 2014-09-11 08:45:29 Multivariate statistics Data analysis Singular value decomposition Principal component analysis Bayesian statistics Estimation theory Data assimilation Covariance matrix Eigenvalues and eigenvectors Statistics Algebra Mathematics
262	Optimal Capital Allocation: Mean-Variance Models Krzysztof M. Ostaszewski Department of Mathematics Illinois State University, Normal, IL, USA [removed] Maochao Xu Add to Reading List Source URL: www.aria.org Language: English - Date: 2014-11-13 04:27:01 Fourier analysis Multivariate statistics Normal distribution Variance Multivariate normal distribution Covariance matrix Multivariate Student distribution Multiplier Multivariate random variable Statistics Data analysis Probability theory
263	Journal of Machine Learning Research[removed]2832 Submitted 2/13; Revised 3/14; Published 8/14 Tensor Decompositions for Learning Latent Variable Models Animashree Anandkumar Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2015-01-08 18:02:10 Tensors Matrix theory Data analysis Multilinear algebra Singular value decomposition Symmetric tensor Rank Homogeneous polynomial Covariance matrix Algebra Mathematics Linear algebra
264	C ONTRIBUTED RESEARCH ARTICLE 1 Prinsimp by Jonathan Zhang, Nancy Heckman, Davor Cubranic, Joel G. Kingsolver, Travis Gaydos and J.S. Add to Reading List Source URL: journal.r-project.org Language: English - Date: 2014-09-27 15:20:02 Abstract algebra Data analysis Singular value decomposition Covariance and correlation Principal component analysis Eigenvalues and eigenvectors Variance Covariance matrix Euclidean vector Algebra Mathematics Linear algebra
265	Development of a variational data assimilation system for coupled ice-ocean models and sea ice analysis Seminar CMC, Dorval Add to Reading List Source URL: collaboration.cmc.ec.gc.ca Language: English - Date: 2008-10-29 09:30:22 Data analysis Weather prediction Control theory Data assimilation Ensemble Kalman filter Covariance matrix Global Environmental Multiscale Model Sea ice Variance Statistics Bayesian statistics Estimation theory
266	Optimal Estimation Retrieval of CO2 from AIRS spectra Bill Irion AIRS Science Team Meeting, Oct[removed]With thanks to Susan Sund-Kulawik, John Worden, Add to Reading List Source URL: airs.jpl.nasa.gov Language: English - Date: 2007-11-01 11:20:56 Algebra of random variables Probability theory Optimal estimation Remote sensing Covariance matrix Covariance Variance Kalman filter Statistics Data analysis Covariance and correlation
267	The Annals of Statistics 2012, Vol. 40, No. 4, 1935–1967 DOI: [removed]AOS949 © Institute of Mathematical Statistics, 2012 LATENT VARIABLE GRAPHICAL MODEL SELECTION VIA Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-11-07 21:35:11 Multivariate statistics Data analysis Summary statistics Expectation–maximization algorithm Matrix Latent variable model Multivariate normal distribution Covariance matrix Principal component analysis Statistics Covariance and correlation Statistical models
268	Group symmetry and covariance regularization Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-11-05 20:49:38 Linear algebra Matrices Data analysis Covariance and correlation Probability theory Covariance Multivariate normal distribution Matrix Symmetry Algebra Statistics Mathematics
269	1012 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 3, MARCH 2010 Gaussian Multiresolution Models: Exploiting Sparse Markov and Covariance Structure Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-11-05 20:49:43 Statistical models Probability theory Networks Markov random field Covariance matrix Sparse matrix Matrix Multivariate normal distribution Conjugate prior Statistics Bayesian statistics Graphical models
270	Exploiting Sparse Markov and Covariance Structure in Multiresolution Models Myung Jin Choi MYUNGJIN @ MIT. EDU Venkat Chandrasekaran VENKATC @ MIT. EDU Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-11-05 20:50:41 Covariance and correlation Algebra of random variables Graphical models Covariance matrix Markov random field Multivariate normal distribution Sparse matrix Matrix Normal distribution Statistics Probability theory Data analysis

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