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Variance decomposition
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#	Item
71	CURE 2007 Statistical Modeling of Discrete Features on Jupiter David Holt, Padma Yanamandra-Fisher, and Amy Braverman* Add to Reading List Source URL: www.lacitycollege.edu Language: English - Date: 2012-06-06 00:58:15 Educational psychology Machine learning Principal component analysis Singular value decomposition Jupiter Variance Dimension reduction G factor Infrared Statistics Multivariate statistics Data analysis
72	Package ‘nsprcomp’ July 17, 2014 Version 0.5 Date[removed]Title Non-Negative and Sparse PCA Description This package implements two methods for performing a constrained Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-17 17:54:13 Multivariate statistics Data analysis Singular value decomposition Linear algebra Abstract algebra Principal component analysis Eigenvalues and eigenvectors Matrix Variance Algebra Statistics Mathematics
73	Covariance Recovery from a Square Root Information Matrix for Data Association Michael Kaess CSAIL, Massachusetts Institute of Technology, 32 Vassar St., Cambridge, MA[removed]Frank Dellaert College of Computing, Georgia I Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2012-03-26 23:43:16 Robot control Summary statistics Linear filters Kalman filter Covariance matrix Covariance Cholesky decomposition Normal distribution Variance Statistics Data analysis Covariance and correlation
74	What to Do When Your Hessian Is Not Invertible Alternatives to Model Respecification in Nonlinear Estimation JEFF GILL University of California, Davis Add to Reading List Source URL: gking.harvard.edu Language: English - Date: 2013-02-04 23:42:24 Normal distribution Maximum likelihood Matrix Multivariate normal distribution Cholesky decomposition Point estimation Prior probability Likelihood function Estimator Statistics Estimation theory Variance
75	Statistical Practice Estimators of Relative Importance in Linear Regression Based on Variance Decomposition ¨ Ulrike Gromping Add to Reading List Source URL: prof.beuth-hochschule.de Language: English - Date: 2008-03-14 04:44:48 Coefficient of determination Multicollinearity T-statistic Variance Correlation and dependence Generalized linear model Explained variation Ordinary least squares Statistics Regression analysis Linear regression
76	Residual periodograms for regularization Add to Reading List Source URL: math.nist.gov Language: English - Date: 2009-09-28 14:05:32 Regression analysis Estimation theory Linear algebra Least squares Parametric statistics Tikhonov regularization Variance Singular value decomposition Normal distribution Statistics Algebra Mathematics
77	Learning Bi-clustered Vector Autoregressive Models Tzu-Kuo Huang and Jeff Schneider School of Computer Science, Carnegie Mellon University {tzukuoh,schneide}@cs.cmu.edu Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2013-02-04 21:32:29 Cluster analysis Singular value decomposition Machine learning Hierarchical clustering Variance Eigenvalues and eigenvectors Vector autoregression Mixture model Standard deviation Statistics Data analysis Multivariate statistics
78	Microsoft Word - The PM10-2.5 Model detail.doc Add to Reading List Source URL: www.epa.gov Language: English - Date: 2005-08-23 15:28:57 Numerical linear algebra Cholesky decomposition Operator theory Variance Normal distribution Matrix Mathcad Statistics Mathematics Mathematical analysis
79	Full Regularization Path for Sparse Principal Component Analysis Alexandre d’Aspremont ORFE, Princeton University, Princeton NJ 08544, USA. [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:24:18 Matrix theory Singular value decomposition Data analysis Operations research Principal component analysis Semidefinite programming Eigenvalues and eigenvectors Variance Linear programming Algebra Mathematics Linear algebra
80	Accepted by Journal of Multivariate Analysis Sparse Principal Component Analysis via Regularized Low Rank Matrix Approximation Haipeng Shen∗and Jianhua Z. Huang† June 7, 2007 Add to Reading List Source URL: www.stat.tamu.edu Language: English - Date: 2007-08-08 12:13:02 Multivariate statistics Data analysis Singular value decomposition Matrix theory Principal component analysis Eigenvalues and eigenvectors Covariance matrix Variance Matrix Algebra Statistics Linear algebra