Results 61 to 70 of about 173 (111)

The Almon Liu-Type M-Estimator for the Distributed Lag Models in the Presence of Multicollinearity and Outliers [PDF]

The Almon method is widely used for the estimation of the distributed lag models (DLM). The advantage of using the Almon technique lies in its capability to avoid some serious problems that may arise from the direct application of ordinary least squares (
Ali, Nasir, Aslam, Muhammad, Imdad Ullah, Muhammad, Majid, Abdul   +3 more
core   +2 more sources

A New Ridge – type in the Bell Regression Model [PDF]

In scenario analysis, collinearity is a big issue in analyzing such relationship as between the response variable and several explanatory variables. As for these difficulties, the linear regression model, often traditionally, offers a range of shrinkage ...
Algamal, Zakariya Yahya, Alsarraf, Israa
core   +3 more sources

A New Kibria-Lukman-Type Estimator for Poisson Regression Models

Acta Infologica
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 Estimator (MLE).
Cemal Çiçek, Kadri Ulaş Akay
doaj   +1 more source

Handling Multicollinearity and Outliers in Logistic Regression Using the Robust Kibria–Lukman Estimator

Axioms
Logistic regression models encounter challenges with correlated predictors and influential outliers. This study integrates robust estimators, including the Bianco–Yohai estimator (BY) and conditionally unbiased bounded influence estimator (CE), with the ...
Adewale F. Lukman, Suleiman Mohammed, Olalekan Olaluwoye, Rasha A. Farghali   +3 more
doaj   +1 more source

A Hybrid Liu-Ridge Method of Handling Multicollinearity in Linear Regression Models [PDF]

Multicollinearity is a critical challenge in linear regression analysis, causing instability and unreliability in Ordinary Least Squares (OLS) estimates when independent variables are highly correlated.
Adejumo T. J., Olalere A. O., Olatayo T. O.   +2 more
core   +1 more source

Robust-stein estimator for overcoming outliers and multicollinearity. [PDF]

Sci Rep, 2023
Lukman AF, Farghali RA, Kibria BMG, Oluyemi OA.   +3 more
europepmc   +1 more source

On Some Ridge Regression Estimators for Logistic Regression Models [PDF]

, 2018
The purpose of this research is to investigate the performance of some ridge regression estimators for the logistic regression model in the presence of moderate to high correlation among the explanatory variables.
Williams, Ulyana P
core   +1 more source

A new shrinkage estimator in negative binomial regression model [PDF]

The ridge estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The negative binomial regression model (NBRM) is a well-known model in application when the response variable is a ...
Algamal, Zakariya Yahya, Ismael, Hasnaa Ahmed   +1 more
core   +3 more sources

Ridge Estimation’s E�ectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations [PDF]

, 2021
The goal of this research is to compare multiple linear regression coe cient estimation technique with multicollinearity. In order to quantify the e ectiveness of estimations by the mean of average mean square error, the ordinary least squares technique
Adedotun, Adedayo F., Obadina, O. G., Odusanya, Oluwaseun A.   +2 more
core  

Introduction to the Vol. 50, No. 2, 2023. [PDF]

Behaviormetrika, 2023
Ueno M.
europepmc   +1 more source