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Variance decomposition
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31	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
32	694 Journal of the American Statistical Association, June 2009 Discussion Boaz NADLER Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2009-06-16 05:02:26 Data analysis Singular value decomposition Covariance and correlation Principal component analysis Linear algebra Eigenvalues and eigenvectors Covariance matrix Matrix Variance Statistics Algebra Multivariate statistics
33	Ch.2 Principal component analysis (PCA) Books on PCA by Jolliffe (2002), Preisendorfer[removed]PCA also called empirical orthogonal function (EOF) analysis. 2.1 Geometric approach to PCA [Book, Sect[removed]Dataset with Add to Reading List Source URL: www.ocgy.ubc.ca Language: English - Date: 2013-08-25 01:58:52 Data analysis Singular value decomposition Covariance and correlation Multivariate statistics Linear algebra Principal component analysis Covariance Eigenvalues and eigenvectors Variance Statistics Algebra Mathematics
34	637 Landscape Ecology 17: 637–646, 2002. © 2002 Kluwer Academic Publishers. Printed in the Netherlands. Hierarchical, Multi-scale decomposition of species-environment Add to Reading List Source URL: www.umass.edu Language: English - Date: 2009-09-07 14:24:33 Regression analysis Biogeography Ecology Restricted randomization Multivariate statistics Explained variation Decomposition Landscape ecology Patch dynamics Statistics Data analysis Analysis of variance
35	Multivariate Eigenvalue Problem: Algebraic Theory and Power Method Moody T. Chu and J. Loren Watterson Add to Reading List Source URL: www4.ncsu.edu Language: English - Date: 2004-12-09 14:07:24 Data analysis Multivariate statistics Singular value decomposition Algebra of random variables Covariance matrix Eigenvalues and eigenvectors Covariance Canonical correlation Variance Statistics Algebra Covariance and correlation
36	A tutorial on Principal Components Analysis Lindsay I Smith February 26, 2002 Chapter 1 Add to Reading List Source URL: openbio.sourceforge.net Language: English - Date: 2002-11-27 18:21:20 Summary statistics Singular value decomposition Multivariate statistics Principal component analysis Covariance matrix Eigenvalues and eigenvectors Variance Covariance Standard deviation Statistics Data analysis Covariance and correlation
37	Figure 1.2.1: Variance Decomposition of Real Credit Growth to the Private Sector1 (In percent, after 4 quarters) Capital Flows 50 Net capital flows Add to Reading List Source URL: www.imf.org Language: English - Date: 2014-04-22 16:30:32
38	Working Paper[removed]A Simple One-Sided Test When the Covariance Matrix Has Non-Negative Eigenvectors Zeng-Hua Lu Centre for Regulation and Market Analysis, Add to Reading List Source URL: www.unisa.edu.au Language: English - Date: 2012-03-25 19:15:15 Singular value decomposition Linear algebra Matrix theory Design of experiments Eigenvalues and eigenvectors Variance Matrix Covariance matrix Model theory Statistics Algebra Data analysis
39	Issues with the Application of Empirical Mode Decomposition Analysis Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 18:39:07 Hilbert–Huang transform Mathematical sciences Spline Hilbert spectral analysis Hilbert spectrum Variance Time series Stationary process Signal processing Statistics Applied mathematics
40	Data assimilation workshop 3D-Var exercise Prepared by Junjie Liu July 26th, Add to Reading List Source URL: www.jcsda.noaa.gov Language: English - Date: 2007-08-01 12:24:51 Estimation theory Bayesian statistics Algebra of random variables Covariance Data assimilation Variance Ensemble Kalman filter Two-dimensional singular value decomposition Statistics Covariance and correlation Data analysis