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Jackknifing the Ridge Regression Estimator: A Revisit.
Khurana, Mansi +2 more
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Linearized Ridge Regression Estimator in Linear Regression
Communications in Statistics - Theory and Methods, 2011In this article, we aim to study the linearized ridge regression (LRR) estimator in a linear regression model motivated by the work of Liu (1993). The LRR estimator and the two types of generalized Liu estimators are investigated under the PRESS criterion.
Xu-Qing Liu, Feng Gao
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On the almost unbiased ridge regression estimator
Communications in Statistics - Simulation and Computation, 1988The purpose of this paper is two-fold. One is to compare the almost unbiased generalized ridge regression (AUGRR) estimator proposed by Singh, Chaubey and Dwivedi (1986) with the generalized ridge regression (GRR) estimator and with the ordinary least squares (OLS) estimator in terms of the mean squared error criterion.
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Ridge Estimators in Logistic Regression
Applied Statistics, 1992Summary: In this paper it is shown how ridge estimators can be used in logistic regression to improve the parameter estimates and to diminish the error made by further predictions. Different ways to choose the unknown ridge parameter are discussed. The main attention focuses on ridge parameters obtained by cross-validation.
le Cessie, S., van Houwelingen, J. C.
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Modified Ridge Regression Estimators
Communications in Statistics - Theory and Methods, 2013Ridge regression is a variant of ordinary multiple linear regression whose goal is to circumvent the problem of predictors collinearity. It gives up the Ordinary Least Squares (OLS) estimator as a method for estimating the parameters [] of the multiple linear regression model [] .
G. Khalaf +2 more
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Poisson regression diagnostics with ridge estimation
Communications in Statistics - Simulation and Computation, 2021Influential observations influence the Poisson regression model (PRM) inferences. There are the situations in the PRM, where the explanatory variables are correlated and influential observations oc...
Aamna Khan +2 more
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Ridge estimation in logistic regression
Communications in Statistics - Simulation and Computation, 1988The variance of the Maximum Likelihood Estimator (MLE) of the slope parameter in a logistic regression model becomes large as the degree of collinearity among the explanatory variables increases. In a Monte Carlo study, we observed that a ridge type estimator is at least as good as, and often much better than, the MLE in terms of Total and Prediction ...
A. H. Lee, M. J. Silvapulle
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A Tobit Ridge Regression Estimator
Communications in Statistics - Theory and Methods, 2013This article analyzes the effects of multicollienarity on the maximum likelihood (ML) estimator for the Tobit regression model. Furthermore, a ridge regression (RR) estimator is proposed since the mean squared error (MSE) of ML becomes inflated when the regressors are collinear. To investigate the performance of the traditional ML and the RR approaches
G. Khalaf +3 more
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Inequality constrained ridge regression estimator
Statistics & Probability Letters, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Toker S. +2 more
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