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AND REGRESSION COEFFICIENTS By
, 2015
"... Given a sample from a biviariate distribution, consider the problem of testing independence. A permutation test using the sample correlation is known to be an exact level α test. However, when used to test the null hypothesis that the samples are uncorrelated, the permutation test can have rejectio ..."
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of the randomization distribution. We will also present asymptotically robust randomization tests for regression coefficients, including a result based on a modified procedure of Freedman and Lane (1983). Simulations and empirical applications are included.
: Regression coefficient
"... MIT 4/28/2008Plan of the Lecture • Demographic forecasting is a machine learning problem • Solving the problem in the Bayesian/ regularization framework • A closer look at one dimensional priors • A closer look at the smoothness parameter • Examples/Demos ..."
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MIT 4/28/2008Plan of the Lecture • Demographic forecasting is a machine learning problem • Solving the problem in the Bayesian/ regularization framework • A closer look at one dimensional priors • A closer look at the smoothness parameter • Examples/Demos
Regression coefficient b (slope)
"... Regression coefficient a (intercept) t (for b = 1) for n 2 degrees of freedom ..."
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Regression coefficient a (intercept) t (for b = 1) for n 2 degrees of freedom
Partial Regression Coefficients
"... The partial regression coefficient is also called regression coefficient, regression weight, partial regression weight, slope coefficient or partial slope coefficient. It is used in the context of multiple linear regression (mlr) analysis and gives the amount by which the dependent variable (DV) inc ..."
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The partial regression coefficient is also called regression coefficient, regression weight, partial regression weight, slope coefficient or partial slope coefficient. It is used in the context of multiple linear regression (mlr) analysis and gives the amount by which the dependent variable (DV
Efficient estimators for regressing regression coefficients.
 American Statistician,
, 1974
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THE PARTIAL REGRESSION COEFFICIENTS IN PEDIGREE EVALUATION
"... The method described by MOSTAGEER (1970) for assessing the efficiency of ancestorrecords was used to derive the partial regression coefficients for traits expressed on both sexes and for sexlimited characters. The regular cases in which all the measurable animals in the T available generations of a ..."
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The method described by MOSTAGEER (1970) for assessing the efficiency of ancestorrecords was used to derive the partial regression coefficients for traits expressed on both sexes and for sexlimited characters. The regular cases in which all the measurable animals in the T available generations
Estimation of Regression Coefficients with Unequal Probability
"... We compare alternative estimators for regression coefficients estimated with data from a complex survey. The ordinary least squares estimator is a common choice of researchers, but under an informative design, the ordinary least squares estimator is biased. The probability weighted estimator is co ..."
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We compare alternative estimators for regression coefficients estimated with data from a complex survey. The ordinary least squares estimator is a common choice of researchers, but under an informative design, the ordinary least squares estimator is biased. The probability weighted estimator
Least angle regression
, 2004
"... The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope to s ..."
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Cited by 1326 (37 self)
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implements the Lasso, an attractive version of ordinary least squares that constrains the sum of the absolute regression coefficients; the LARS modification calculates all possible Lasso estimates for a given problem, using an order of magnitude less computer time than previous methods. (2) A different LARS
Spurious Regressions in Econometrics
 Journal of Econometrics
, 1974
"... It is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the DurbinWatson statistic. We f ..."
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Cited by 800 (6 self)
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It is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the DurbinWatson statistic. We
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