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Dimensional analysis
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#	Item
741	Statistical Science 2012, Vol. 27, No. 4, 538–557 DOI: [removed]STS400 © Institute of Mathematical Statistics, 2012 A Unified Framework for High-Dimensional Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2013-11-23 00:17:42 Econometrics M-estimators Regression analysis Parametric model Maximum likelihood Fisher information Loss function Linear regression Consistent estimator Statistics Estimation theory Statistical theory
742	On Robust Estimation of High Dimensional Generalized Linear Models Eunho Yang Ambuj Tewari Pradeep Ravikumar Department of Computer Science Department of Statistics Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2013-06-28 15:47:04 Robust statistics Econometrics Statistical theory Linear regression Robust regression Generalized linear model Poisson regression Estimator Ordinary least squares Statistics Regression analysis Estimation theory
743	Enlargement of a low-dimensional stochastic web S.M. Soskin∗,†,‡, I.A. Khovanov∗∗,‡ , R. Mannella§ and P.V.E. McClintock‡ ∗ Institute of Semiconductor Physics, 03028 Kiev, Ukraine † Add to Reading List Source URL: eprints.lancs.ac.uk Language: English - Date: 2011-01-27 18:43:04 Dynamical systems Quantum mechanics Spintronics Superlattice Perturbation theory Separatrix Chaos theory Effective mass Hamiltonian mechanics Physics Mathematical analysis Condensed matter physics
744	A unified framework for high-dimensional analysis of M -estimators with decomposable regularizers Sahand Negahban Department of EECS UC Berkeley sahand [removed] Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2009-11-18 14:28:49 Logic Statistical theory Regression analysis Maximum likelihood Linear regression Entailment Projection Loss function Dimensional analysis Statistics Estimation theory Econometrics
745	A Dirty Model for Multi-task Learning Ali Jalali University of Texas at Austin [removed] Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2010-11-05 21:08:25 Econometrics Linear regression Sparse approximation Dimensional analysis Regularization Normal distribution Statistics Regression analysis Estimation theory
746	Technical note: How Most Similar Groups are formed What are Most Similar Groups? Most Similar Groups (MSGs) are groups of local areas that have been found to be the most similar to each other using statistical methods, b Add to Reading List Source URL: www.justiceinspectorates.gov.uk Language: English - Date: 2014-11-26 12:15:56 Multivariate statistics Logical syntax Variables Standard deviation Correlation and dependence Dimensional analysis Principal component analysis Quartile Unemployment Statistics Data analysis Summary statistics
747	The Cyclical Component of Labor Market Polarization and Jobless Recoveries in the US Paul Gaggl, and Sylvia Kaufmann Working Paper[removed]This discussion paper series represents research work-in-progress and is distribut Add to Reading List Source URL: www.szgerzensee.ch Language: English - Date: 2014-05-05 12:02:13 Fourier analysis One Trigonometry Unit circle Dimensional analysis Unemployment Labour economics Markov chain Mathematical analysis Geometry Analytic geometry Circles
748	Organisation Internationale des Scénografes, Techniciens et Architectes de Théâtre International Organization of Scenographers, Theatre Architects and Technicians theatre atlas Metric Version 1 General information Add to Reading List Source URL: www.ccdewerf.be Language: English - Date: 2013-11-26 10:19:26 Proscenium Dimensional analysis Knowledge Learning Culture Parts of a theatre Stagecraft Stage
749	Technical note: How Most Similar Groups are formed What are Most Similar Groups? Most Similar Groups (MSGs) are groups of local areas that have been found to be the most similar to each other using statistical methods, b Add to Reading List Source URL: www.justiceinspectorates.gov.uk Language: English - Date: 2014-11-26 12:15:56 Multivariate statistics Logical syntax Variables Standard deviation Correlation and dependence Dimensional analysis Principal component analysis Quartile Unemployment Statistics Data analysis Summary statistics
750	N-Dimensional Principal Component Analysis Hongchuan YU and Jian J. ZHANG NCCA, Bournemouth University Abstract In this paper, we first briefly introduce the multidimensional Principal Component Analysis (PCA) techniques Add to Reading List Source URL: eprints.bournemouth.ac.uk Language: English - Date: 2010-07-28 12:35:21 Singular value decomposition Multivariate statistics Matrix theory Functional analysis Principal component analysis Two-dimensional singular value decomposition Higher-order singular value decomposition Eigenvalues and eigenvectors Singular value Algebra Linear algebra Mathematics

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