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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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On the estimation of Bell regression model using ridge estimator
Communications in Statistics - Simulation and Computation, 2021The bell regression is used, when the response variable is in the form of counts with over dispersion.
Muhammad Amin +2 more
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A restricted gamma ridge regression estimator combining the gamma ridge regression and the restricted maximum likelihood methods of estimation [PDF]
Journal of Statistical Computation and Simulation, 2022 In this article, we propose a restricted gamma ridge regression estimator (RGRRE) by combining the gamma ridge regression (GRR) and restricted maximum likelihood estimator (RMLE) to combat multicollinearity problem for estimating the parameter beta in ...
Muhammad Qasim +2 more
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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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Beta ridge regression estimators: simulation and application
Communications in Statistics - Simulation and Computation, 2021The beta regression model is commonly used when analyzing data that come in the form of rates or percentages.
Mohamed Reda Abonazel, Ibrahim M. Taha
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Shrinkage Ridge Estimators in Linear Regression
Communications in Statistics - Simulation and Computation, 2013The problem of estimation of the regression coefficients in a multiple regression model (MRM) is considered under multicollinearity situation. Further it is suspected that the regression coefficients may be restricted to a subspace. In this approach, we present the estimators of the regression coefficients combining the idea of preliminary test ...
Mohammad Arashi +2 more
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New Ridge Regression Estimator in Semiparametric Regression Models
Communications in Statistics - Simulation and Computation, 2015In the context of ridge regression, the estimation of shrinkage parameter plays an important role in analyzing data. Many efforts have been put to develop the computation of risk function in different full-parametric ridge regression approaches using eigenvalues and then bringing an efficient estimator of shrinkage parameter based on them.
Mahdi Roozbeh, Mohammad Arashi
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Improved ridge regression estimators for the logistic regression model
Computational Statistics, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
A. K. Md. Ehsanes Saleh +1 more
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Robust ridge and robust Liu estimator for regression based on the LTS estimator [PDF]
Journal of Applied Statistics, 2013 WOS: 000317837200012In the multiple linear regression analysis, the ridge regression estimator and the Liu estimator are often used to address multicollinearity.
Özlem Alpu, Berna Yazici
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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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