On the performance of the poisson and the negative binomial ridge predictors

DOI10.1080/03610918.2017.1324978OpenAlexW2613018821MaRDI QIDQ5084952

Selahattin Kaçıranlar, Issam Dawoud

Publication date: 29 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2017.1324978

zbMATH Keywords

Monte Carlo simulationsmulticollinearityprediction mean square errornegative binomial regression predictorPoisson regression predictor

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items

A modified one parameter Liu estimator for Conway-Maxwell Poisson response model ⋮ New modified two-parameter Liu estimator for the Conway–Maxwell Poisson regression model ⋮ Two parameter estimators for the Conway–Maxwell–Poisson regression model ⋮ Improved two-parameter estimators for the negative binomial and Poisson regression models ⋮ Robust Dawoud–Kibria estimator for handling multicollinearity and outliers in the linear regression model

Cites Work

• Linear models. Least squares and alternatives
• Stein-rule estimation under an extended balanced loss function
• Evaluation of the Predictive Performance of the Liu Estimator
• Ridge regression:some simulations
• A new class of blased estimate in linear regression
• Predictive Performance of the Methods of Restricted and Mixed Regression Estimators
• The Predictive Performance Evaluation of Biased Regression Predictors With Correlated Errors
• Performance of Some New Ridge Regression Estimators
• Improved Predictions in Linear Regression Models with Stochastic Linear Constraints
• Bayesian Estimation of Regression Coefficients Under Extended Balanced Loss Function