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Covariance matrix
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161	Package ‘corrgram’ February 19, 2015 Type Package Title Plot a Correlogram Version 1.7 Date Add to Reading List Source URL: cran.r-project.org Language: English Covariance and correlation Multivariate statistics Statistical dependence Data analysis Principal component analysis Singular value decomposition Matrix Correlation and dependence SAS Statistics Information Science
162	ON THE CAPACITY OF LINEAR VECTOR GAUSSIAN CHANNELS WITH MAGNITUDE KNOWLEDGE AND PHASE UNCERTAINTY ´ Lagunas∗ Miquel Payar´o∗, Ami Wiesel†, Jinhong Yuan‡ , Miguel Angel ∗ Add to Reading List Source URL: www.ece.ust.hk Language: English - Date: 2007-03-12 05:34:21 Information theory Matrices Matrix theory Covariance and correlation Radio resource management Covariance matrix MIMO Eigenvalues and eigenvectors Channel state information Algebra Linear algebra Mathematics
163	egu_logo_without_circle_grey Add to Reading List Source URL: www.geosci-model-dev.net Language: English - Date: 2014-12-04 04:34:54 Data analysis Covariance and correlation Linear algebra Control theory Estimation theory Covariance Data assimilation Matrix Cholesky decomposition Statistics Algebra Mathematics
164	Coastal Characterization Using EO-1 Hyperion Data Dr. Hsiao-hua K. Burke MIT Lincoln Laboratory EO-1 SVT MeetingNovember 2002 Add to Reading List Source URL: www.cossa.csiro.au Language: English - Date: 2002-12-15 23:27:20 Multivariate statistics Data analysis Singular value decomposition Linear algebra Matrix theory Principal component analysis Covariance matrix Eigenvalues and eigenvectors Dimension reduction Algebra Statistics Mathematics
165	Geosci. Model Dev., 4, 299–316, 2011 www.geosci-model-dev.netdoi:gmd © Author(sCC Attribution 3.0 License. Geoscientific Add to Reading List Source URL: www.geosci-model-dev.net Language: English - Date: 2014-12-04 04:00:34 Control theory Data analysis Linear filters Data assimilation Ensemble Kalman filter Kalman filter Covariance matrix Matrix Covariance Statistics Estimation theory Bayesian statistics
166	Finite sample approximation results for principal component analysis: a matrix perturbation approach Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2009-01-06 09:59:49 Data analysis Multivariate statistics Matrix theory Singular value decomposition Principal component analysis Eigenvalues and eigenvectors Covariance matrix Multivariate normal distribution Normal distribution Statistics Algebra Linear algebra
167	On the Privacy Preserving Properties of Random Data Perturbation Techniques Hillol Kargupta and Souptik Datta Computer Science and Electrical Engineering Department University of Maryland Baltimore County Baltimore, Mary Add to Reading List Source URL: www.csee.umbc.edu Language: English - Date: 2006-07-26 01:44:00 Probability theory Data analysis Matrices Mathematical physics Multivariate statistics White noise Matrix Eigenvalues and eigenvectors Covariance matrix Statistics Algebra Mathematics
168	Pattern Recognition[removed] – 125 www.elsevier.com/locate/patcog Directional features in online handwriting recognition夡 Claus Bahlmann∗ Siemens Corporate Research, Inc., 755 College Road East, Princeton, NJ Add to Reading List Source URL: lmb.informatik.uni-freiburg.de Language: English - Date: 2012-06-18 23:39:56 Probability theory Statistical models Multivariate statistics Gaussian function Normal distribution Von Mises distribution Variance Multivariate normal distribution Covariance matrix Statistics Data analysis Directional statistics
169	Canonical Correlation Clarified by Singular Value Decomposition William H. Press May 28, 2011 The Setup You have a number n of data points, each one of which is a paired measurement Add to Reading List Source URL: nr.com Language: English - Date: 2011-05-28 14:30:36 Numerical linear algebra Matrix theory Multivariate statistics Covariance and correlation Singular value decomposition Canonical correlation Principal component analysis Matrix Variance Algebra Linear algebra Mathematics
170	Chapter 4: Formulating the Predictor Variables Chapter 3 focused on the construction of a gridded daily rainfall dataset, which will form the response variable in the statistical model that is the goal of this thesis. Th Add to Reading List Source URL: www.cru.uea.ac.uk Language: English - Date: 2009-12-22 04:43:50 Data analysis Multivariate statistics Singular value decomposition Abstract algebra Linear algebra Principal component analysis Eigenvalues and eigenvectors Covariance matrix Variance Statistics Algebra Mathematics

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