New shrinkage parameters for the inverse Gaussian Liu regression

DOI10.1080/03610926.2020.1791339OpenAlexW3043460225MaRDI QIDQ5081051

Muhammad Qasim, Khalid Naveed, Saima Afzal, Muhammad Amin

Publication date: 1 June 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2020.1791339

zbMATH Keywords

mean squared errorMonte Carlo simulationmean absolute errorinverse Gaussian regressioninverse Gaussian-Liu regression estimator

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (8)

New ridge estimators in the inverse Gaussian regression: Monte Carlo simulation and application to chemical data ⋮ Two-parameter estimator for the inverse Gaussian regression model ⋮ On the performance of some biased estimators in the gamma regression model: simulation and applications ⋮ Generalized two-parameter estimators in the multinomial logit regression model: methods, simulation and application ⋮ Developed first-order approximated estimators for the gamma distributed response variable ⋮ Modified ridge-type estimator for the inverse Gaussian regression model ⋮ Inverse Gaussian Liu-type estimator ⋮ Two parameter Ridge estimator in the inverse Gaussian regression model

Uses Software

• glm

Cites Work

• Modified restricted Liu estimator in logistic regression model
• Performance of some ridge estimators for the gamma regression model
• Liu estimation in generalized linear models: application on gamma distributed response variable
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• A Purchase Incidence Model with Inverse Gaussian Interpurchase Times
• On ordinary ridge regression in generalized linear models
• A new class of blased estimate in linear regression
• Performance of Some New Ridge Regression Estimators
• Some Liu and ridge-type estimators and their properties under the ill-conditioned Gaussian linear regression model
• On the performance of some new Liu parameters for the gamma regression model
• A new Poisson Liu Regression Estimator: method and application
• Performance of some new Liu parameters for the linear regression model
• A new Liu-type estimator for the Inverse Gaussian Regression Model
• Developing a Liu estimator for the negative binomial regression model: method and application
• Performance of Some Weighted Liu Estimators for Logit Regression Model: An Application to Swedish Accident Data
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
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