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Jackknifing the Ridge Regression Estimator: A Revisit.

Khurana, Mansi, Chaubey, Yogendra P., Chandra, Shalini   +2 more
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Ridge Estimators in Logistic Regression

Applied Statistics, 1992
Summary: 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, 2013
Ridge 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, Kristofer Månsson, Ghazi Shukur   +2 more
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Poisson regression diagnostics with ridge estimation

Communications in Statistics - Simulation and Computation, 2021
Influential 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, Muhammad Aman Ullah, Muhammad Amin   +2 more
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Linearized Ridge Regression Estimator in Linear Regression

Communications in Statistics - Theory and Methods, 2011
In 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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Ridge estimation in logistic regression

Communications in Statistics - Simulation and Computation, 1988
The 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, 2013
This 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, K. Månsson, P. Sjölander, G. Shukur   +3 more
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Inequality constrained ridge regression estimator

Statistics & Probability Letters, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Toker S., Üstündag Şiray G., Kaçiranlar S.   +2 more
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Minimax Linear Regression Estimators With Application to Ridge Regression

Technometrics, 1982
This article considers minimax linear estimation of β in the multiple linear-regression model Y = Xβ + ξ. Some results from European publications are referenced and summarized and some new results are given. These minimax estimators of β can also be classified as ridgeregression estimators with nonstochastic ridge parameters.
Lawrence Peele, Thomas P. Ryan
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