Penalized and ridge-type shrinkage estimators in Poisson regression model

DOI10.1080/03610918.2020.1730402zbMath1497.62183OpenAlexW3009992683MaRDI QIDQ5867447

Reza Arabi Belaghi, Mehri Noori Asl, Hossein Bevrani

Publication date: 14 September 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2020.1730402

zbMATH Keywords

efficiencyshrinkage estimatorridge regressionmulticollinearityLassoelastic-net

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Parametric inference under constraints (62F30)

Related Items (2)

On the James-Stein estimator for the poisson regression model ⋮ Generalized two-parameter estimators in the multinomial logit regression model: methods, simulation and application

Uses Software

• glmnet

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Lasso-type recovery of sparse representations for high-dimensional data
• Least angle regression. (With discussion)
• Ridge-type shrinkage estimators in generalized linear models with an application to prostate cancer data
• Improved ridge regression estimators for the logistic regression model
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• A simulation study of ridge and other regression estimators
• On ordinary ridge regression in generalized linear models
• Performance of Some New Ridge Regression Estimators
• Regularization and Variable Selection Via the Elastic Net
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

This page was built for publication: Penalized and ridge-type shrinkage estimators in Poisson regression model