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Linear least squares
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#	Item
891	MEMORANDUM Date: August 23, 2001 Add to Reading List Source URL: epa.gov Language: English - Date: 2012-09-12 12:06:46 Diesel fuel Least squares Linear regression Dummy variable Hexadecane Errors and residuals in statistics Conceptual model Statistics Regression analysis Econometrics
892	Package ‘gam’ July 2, 2014 Type Package Title Generalized Additive Models Date[removed]Version[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 11:55:40 Additive model Backfitting algorithm Smoothing Gam Deviance Linear least squares Degrees of freedom Kernel smoother Least squares Statistics Regression analysis Generalized additive model
893	A Graphically Motivated, Non-Calculus Derivation of Formulas for Linear Regression S. M. Zoltek¤ S. S. Dicky Department of Mathematical Sciences and Add to Reading List Source URL: archives.math.utk.edu Language: English - Date: 1997-11-05 00:00:00 Least squares Linear regression Slope Line Distance Least absolute deviations Simple linear regression Statistics Regression analysis Mathematics
894	Simultaneous analysis of Lasso and Dantzig selector Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2010-04-22 01:01:09 Estimation theory Parametric statistics Least squares Linear regression Ordinary least squares Differential of a function Sparse approximation Nonparametric regression Statistics Regression analysis Econometrics
895	WORKING PAPER #31 An Evaluation of Empirical Bayes’ Estimation of ValueAdded Teacher Performance Measures Cassandra M. Guarino, Indiana University Michelle Maxfield, Michigan State University Mark D. Reckase, Michigan Add to Reading List Source URL: education.msu.edu Language: English - Date: 2014-03-11 12:04:45 Linear regression Ordinary least squares Gauss–Markov theorem Generalized least squares Bayes estimator Estimator Bias of an estimator Least squares Fixed effects model Statistics Estimation theory Regression analysis
896	The Lasso Problem and Uniqueness Ryan J. Tibshirani Carnegie Mellon University Abstract The lasso is a popular tool for sparse linear regression, especially for problems in which the number of variables p exceeds the num Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2014-04-03 22:49:13 Mathematical optimization Theoretical computer science Abstract algebra Linear algebra Least squares Lasso Linear programming Convex optimization Vector space Mathematics Algebra Regression analysis
897	Lessard et al. Vol. 25, No. 5 / May[removed]J. Opt. Soc. Am. A 1147 Add to Reading List Source URL: www.cds.caltech.edu Language: English - Date: 2008-04-23 12:56:00 Mathematical analysis Conjugate gradient method Least squares Preconditioner Iterative reconstruction Multigrid method Kalman filter Numerical linear algebra Numerical analysis Mathematics
898	Discussion of ``A significance test for the lasso'' Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2014-05-27 07:57:45 Least squares Prediction interval Causality Nonparametric regression Generalized least squares Simple linear regression Statistics Regression analysis Linear regression
899	Sign-constrained least squares estimation for high-dimensional regression Add to Reading List Source URL: stat.ethz.ch Language: English - Date: 2013-06-05 04:38:23 Estimation theory Parametric statistics Statistical theory Least squares Linear regression Multivariate normal distribution Normal distribution Shrinkage estimator Variance Statistics Regression analysis Econometrics
900	Globally Optimal Estimates for Geometric Reconstruction Problems Fredrik Kahl½ ¾ [removed] ½ Didier Henrion¿ Add to Reading List Source URL: vision.ucsd.edu Language: English - Date: 2005-07-20 12:57:16 Linear matrix inequality Convex optimization Bundle adjustment Semidefinite programming Relaxation Triangulation Polynomial Least squares Matrix Mathematical optimization Mathematics Mathematical analysis

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