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Gauss–Markov theorem
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61	Bernoulli 19(5A), 2013, 1839–1854 DOI: [removed]BEJ432 Optimal variance estimation without estimating the mean function T I E J U N TO N G 1 , YA N Y UA N M A 2 and Y U E D O N G WA N G 3 Add to Reading List Source URL: www.stat.tamu.edu Language: English - Date: 2013-11-05 11:24:58 Statistical theory Least squares Statistical inference Gauss–Markov theorem Normal distribution Ordinary least squares Mean squared error Efficient estimator Bias of an estimator Statistics Estimation theory Regression analysis
62	#117 :: Chandra Calibration Workshop & Chandra 8 Years Symposium :: 2007 Oct 22−25, Huntsville, AL Incorporating Effective Area Uncertainties into Spectral Fitting Vinay Kashyap (SAO), Hyunsook Lee (SAO), Jeremy Drake Add to Reading List Source URL: hea-www.harvard.edu Language: English - Date: 2007-10-30 20:11:49 Gauss–Markov theorem ADP ribosylation factor Markov chain Tral
63	PDF Document Add to Reading List Source URL: media.wiley.com Language: English - Date: 2009-06-10 05:05:20 Ordinary least squares Least squares Gauss–Markov theorem Simple linear regression Seemingly unrelated regressions Linear least squares Coefficient of determination Generalized least squares Errors and residuals in statistics Statistics Regression analysis Linear regression
64	ECONOMETRICS Bruce E. Hansen c 2000, 20131 University of Wisconsin Add to Reading List Source URL: www.ssc.wisc.edu Language: English - Date: 2013-01-21 09:40:27 Linear regression Heteroscedasticity Generalized method of moments Instrumental variable Least squares Quantile regression Vector autoregression Generalized least squares Gauss–Markov theorem Statistics Regression analysis Econometrics
65	ECONOMETRICS Bruce E. Hansen c °2000, 20141 Add to Reading List Source URL: www.ssc.wisc.edu Language: English - Date: 2014-01-03 17:00:28 Statistical inference Estimation theory Parametric statistics Linear regression Heteroscedasticity Least squares Generalized least squares Instrumental variable Gauss–Markov theorem Statistics Regression analysis Econometrics
66	ECONOMETRICS Bruce E. Hansen c °2000, 2001, 2002, 2003, 2004, 20051 University of Wisconsin Add to Reading List Source URL: www.ssc.wisc.edu Language: English - Date: 2005-01-19 11:23:10 Linear regression Heteroscedasticity Instrumental variable Least squares Bootstrapping Variance Resampling Gauss–Markov theorem Normal distribution Statistics Regression analysis Econometrics
67	ECONOMETRICS Bruce E. Hansen c 2000, 20121 University of Wisconsin Add to Reading List Source URL: www.ssc.wisc.edu Language: English - Date: 2012-01-18 12:38:22 Linear regression Heteroscedasticity Generalized method of moments Instrumental variable Least squares Quantile regression Vector autoregression Generalized least squares Gauss–Markov theorem Statistics Regression analysis Econometrics
68 8960,720,3<: 960 10 = 96; 720 7.5 = 96 , so this is 96 dpi. L LatheInput1 = Import@"C:\\Users\\3000\\Des" title="H PowerPoint letter is 10 x 7.5", by its ruler - apparently 12" margins are not shown. Imported gif is -> 8960,720,3<: 960 10 = 96; 720 7.5 = 96 , so this is 96 dpi. *L LatheInput1 = Import@"C:\\Users\\3000\\Des" class="img-responsive img-polaroid">	H* PowerPoint letter is 10 x 7.5", by its ruler - apparently 12" margins are not shown. Imported gif is -> 8960,720,3<: 960 10 = 96; 720 7.5 = 96 , so this is 96 dpi. L LatheInput1 = Import@"C:\\Users\\3000\\Des Add to Reading List Source URL: www.youvan.com Language: English* - Date: 2014-05-25 12:14:47 Gauss–Markov theorem 8I 8J
69	THE CLASSICAL LINEAR REGRESSION MODEL Herman J. Bierens Pennsylvania State University September 1, 2002 1. Add to Reading List Source URL: econ.la.psu.edu Language: English - Date: 2002-09-02 03:21:39 Normal distribution Gauss–Markov theorem Multivariate normal distribution Residual sum of squares Explained sum of squares Statistics Regression analysis Least squares
70	Archaeal origin of tubulin Add to Reading List Source URL: www.ncbi.nlm.nih.gov Language: English Least squares T-statistic Linear regression Errors-in-variables models Errors and residuals in statistics Deming regression Regression dilution Gauss–Markov theorem Confidence interval Statistics Regression analysis Prediction interval