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Ordinary least squares
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331	Hydrol. Earth Syst. Sci., 13, 1907–1920, 2009 www.hydrol-earth-syst-sci.net/ © Author(sThis work is distributed under the Creative Commons Attribution 3.0 License. Hydrology and Add to Reading List Source URL: www.hydrol-earth-syst-sci.net Language: English - Date: 2014-12-04 02:31:55 Regression analysis Econometrics Estimation theory Kriging Multivariate interpolation Variogram Linear regression Ordinary least squares Statistics Interpolation Geostatistics
332	School of Economics Working Papers ISSN[removed]On Bootstrap Validity Add to Reading List Source URL: economics.adelaide.edu.au Language: English - Date: 2014-08-10 21:21:47 Regression analysis Econometrics Bootstrapping Symbol Ordinary least squares Resampling Central limit theorem Hausman test Statistics Statistical inference Statistical tests
333	Classical Decomposition Model Revisited: I • recall classical decomposition model for time series Yt, namely, Yt = mt + st + Wt, (∗) Add to Reading List Source URL: faculty.washington.edu Language: English - Date: 2015-03-11 12:29:22 Ordinary least squares Generalized least squares Linear regression Linear least squares Least squares Residual sum of squares Covariance Errors and residuals in statistics Heteroscedasticity-consistent standard errors Statistics Regression analysis Gauss–Markov theorem
334	Random Forests for the Social Sciences Zachary Jones and Fridolin Linder∗ Abstract Machine learning techniques gain in popularity in many disciplines and increased computational power allows for easy implementation of Add to Reading List Source URL: zmjones.com Language: English - Date: 2015-04-12 13:23:45 Decision tree learning Resampling Least squares Ordinary least squares Variance Degrees of freedom Random variable Bootstrapping Errors and residuals in statistics Statistics Regression analysis Random forest
335	20th International Congress on Modelling and Simulation, Adelaide, Australia, 1–6 December 2013 www.mssanz.org.au/modsim2013 Generalised linear model and analysis of cereal plant biomass M. Cespedes a, J. Cai b Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-11-19 22:01:55 Linear regression Ordinary least squares Deviance Least squares Generalized linear model Nonlinear regression Outline of regression analysis Focused information criterion Statistics Regression analysis Akaike information criterion
336	Robust Frequency Estimation Using Elemental Sets∗ Gordon K. Smyth Department of Mathematics, University of Queensland, Australia 4072 Douglas M. Hawkins Department of Applied Statistics Add to Reading List Source URL: www.statsci.org Language: English - Date: 2005-09-26 22:05:43 Statistical theory Econometrics Least squares M-estimator Ordinary least squares Mean squared error Linear regression Estimator Least trimmed squares Statistics Estimation theory Regression analysis
337	Simple Linear Regression (SLR) Dr. Saed Sayad University of Toronto[removed]removed] Add to Reading List Source URL: chem-eng.utoronto.ca Language: English - Date: 2010-02-25 17:26:47 Simple linear regression Residual sum of squares Ordinary least squares Least squares Errors and residuals in statistics Partial regression plot Statistics Regression analysis Linear regression
338	General Linear Least Squares James R. Graham[removed]Equations of condition Suppose we consider a model to describe a data set (xi, yi) where y = y(x) and the function can Add to Reading List Source URL: ugastro.berkeley.edu Language: English - Date: 2009-10-13 18:25:10 Regression analysis Least squares Numerical linear algebra Abstract algebra Linear least squares Degrees of freedom Ordinary least squares Matrix Transpose Algebra Mathematics Linear algebra
339	School of Economics Working Papers ISSN[removed]Specification Tests with Add to Reading List Source URL: economics.adelaide.edu.au Language: English - Date: 2014-08-10 21:21:47 Statistical inference Statistical tests Estimation theory Ordinary least squares Hausman test Instrumental variable Bootstrapping Resampling Endogeneity Statistics Econometrics Regression analysis
340	By Shyunji Takahashi Statistical methods used in the long-forecast at JMA Add to Reading List Source URL: ds.data.jma.go.jp Language: English - Date: 2004-07-05 02:18:38 Linear regression Ordinary least squares Eigenvalues and eigenvectors Forecasting Matrix Least squares Degrees of freedom Orthogonality Multiple correlation Statistics Algebra Regression analysis

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