Robust-stein estimator for overcoming outliers and multicollinearity. [PDF]
Sci Rep, 2023 Lukman AF +3 more
europepmc +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 +1 more
core +3 more sources
Introduction to the Vol. 50, No. 2, 2023. [PDF]
Behaviormetrika, 2023 Ueno M.
europepmc +1 more source
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. +2 more
core
Unbiased K-L estimator for the linear regression model. [PDF]
F1000Res, 2021 Aladeitan B +4 more
europepmc +1 more source
Feasible robust Liu estimator to combat outliers and multicollinearity effects in restricted semiparametric regression mode [PDF]
Regression analysis frequently encounters two issues: multicollinearity among the explanatory variables, and the existence of outliers in the data set.
M. Roozbeh +2 more
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Robust Negative Binomial Regression via the Kibria–Lukman Strategy: Methodology and Application
MathematicsCount regression models, particularly negative binomial regression (NBR), are widely used in various fields, including biometrics, ecology, and insurance.
A. Lukman +5 more
semanticscholar +1 more source
A new class of efficient and debiased two-step shrinkage estimators: method and application. [PDF]
J Appl Stat, 2022 Qasim M +3 more
europepmc +1 more source
A new class of Poisson Ridge-type estimator. [PDF]
Sci Rep, 2023 Ertan E, Akay KU.
europepmc +1 more source
Hybrid principal component regression estimation in linear regression [PDF]
In this paper, the principal component regression (PCR) estimators for regression parameters were studied in a linear regression model. After discussing the advantages and disadvantages of the classical PCR, we put forward three versions of hybrid PCR ...
Jian-Ying Rong, Xu-Qing Liu
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