Results 231 to 240 of about 1,043 (255)

Stratification-based instrumental variable analysis framework for nonlinear effect analysis. [PDF]

Biostatistics
Tian H, Patel A, Burgess S.
europepmc   +1 more source

AI-discovered tuning laws explain neuronal population code geometry

Tilbury R, Kwon D, Haydaroğlu A, Ratliff J, Schmutz V, Carandini M, Miller K, Stachenfeld K, Harris KD.   +8 more
europepmc   +1 more source

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The general expressions for the moments of lawless and wang's ordinary ridge regression estimator

Communications in Statistics - Theory and Methods, 1994
In this paper, we derive the exact general expressions for the moments of an ordinary ridge regression (ORR) estimator for individual regression coefficients in a different way from Firinguetti (1987). Using the derived expressions, we evaluate numerically the first four moments of the ORR estimator, and examine its bias, mean square error, skewness ...
Hideo Kozumi, Kazuhiro Ohtani
exaly   +2 more sources

Bounds of the F-ratio incorporating the ordinary ridge regression estimator

Economics Letters, 1985
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kazuhiro Ohtani
exaly   +2 more sources

Robust two parameter ridge M-estimator for linear regression

Journal of Applied Statistics, 2015
The problem of multicollinearity and outliers in the data set produce undesirable effects on the ordinary least squares estimator. Therefore, robust two parameter ridge estimation based on M-estimator (ME) is introduced to deal with multicollinearity and
Selma Toker
exaly   +2 more sources

Performance of a new ridge regression estimator

Journal of the Association of Arab Universities for Basic and Applied Sciences, 2010
Ridge regression estimator has been introduced as an alternative to the ordinary least squares estimator (OLS) in the presence of multicollinearity. Several studies concerning ridge regression have dealt with the choice of the ridge parameter.
Al-Hassan, Yazid M.,, Yazid M. Al-Hassan, Al-Hassan, Yazid M.   +2 more
exaly   +2 more sources

A new ridge‐type estimator for the linear regression model with correlated regressors

Concurrency Computation Practice and Experience, 2022
Abiola T Owolabi, Kayode Ayinde
exaly