A new improvement Liu-type estimator for the Bell regression model
E Ertan, ZY Algamal, A Erkoç… - … in Statistics-Simulation and …, 2023 - Taylor & Francis
Abstract The Poisson Regression Model (PRM) is a well-known model in applications when
the response variable consists of count data. However, Bell Regression Model (BRM) is …
the response variable consists of count data. However, Bell Regression Model (BRM) is …
Kibria–Lukman Hybrid Estimator for Handling Multicollinearity in Poisson Regression Model: Method and Application
H Alrweili - … Journal of Mathematics and Mathematical Sciences, 2024 - Wiley Online Library
The Poisson regression model (PRM) is a widely used statistical technique for analyzing
count data. However, when explanatory variables in the model are correlated, the estimation …
count data. However, when explanatory variables in the model are correlated, the estimation …
The beta Liu-type estimator: simulation and application
The Beta Regression Model (BRM) is commonly used while analyzing data where the
dependent variable is restricted to the interval $[0, 1] $ for example proportion or probability …
dependent variable is restricted to the interval $[0, 1] $ for example proportion or probability …
Modified Two-Parameter Liu Estimator for Addressing Multicollinearity in the Poisson Regression Model
This study introduces a new two-parameter Liu estimator (PMTPLE) for addressing the
multicollinearity problem in the Poisson regression model (PRM). The estimation of the PRM …
multicollinearity problem in the Poisson regression model (PRM). The estimation of the PRM …
Poisson average maximum likelihood‐centered penalized estimator: A new estimator to better address multicollinearity in Poisson regression
S Li, W Wang, M Yao, J Wang, Q Du, X Li… - Statistica …, 2024 - Wiley Online Library
The Poisson ridge estimator (PRE) is a commonly used parameter estimation method to
address multicollinearity in Poisson regression (PR). However, PRE shrinks the parameters …
address multicollinearity in Poisson regression (PR). However, PRE shrinks the parameters …
Identifying a class of Ridge-type estimators in binary logistic regression models
E Ertan, KU Akay - Statistics, 2024 - Taylor & Francis
In the analysis of logistic regression models, various biased estimators have been proposed
as an alternative to the maximum likelihood estimator (MLE) for estimating model …
as an alternative to the maximum likelihood estimator (MLE) for estimating model …
A New General Ridge-Type Estimator in Linear Regression Models: Accepted-January 2024
In linear regression models, researchers develop new biased estimators to alleviate the
effects of multicollinearity, rather than using the Ordinary Least Squares (OLS) method which …
effects of multicollinearity, rather than using the Ordinary Least Squares (OLS) method which …
A New Kibria-Lukman-Type Estimator for Poisson Regression Models
C Çiçek, KU Akay - Acta Infologica, 2024 - dergipark.org.tr
One of the most important models for the analysis of count data is the Poisson Regression
Model (PRM). The parameter estimates of the PRM are obtained by the Maximum Likelihood …
Model (PRM). The parameter estimates of the PRM are obtained by the Maximum Likelihood …