Results 41 to 50 of about 197,245 (124)
Performance Evaluation of Measures of Central Tendency (MCT) in Tackling Missing Data in Collinear Regressors: A Comparison of Linear Estimators [PDF]
The Egyptian Statistical JournalThe presence of missing data and multicollinearity in regression analysis poses significant challenges to the reliability and accuracy of model estimates.
Abass Taiwo +3 more
doaj +1 more source
Jackknifing K-L estimator in Poisson regression model [PDF]
, 2022 At the point when there is collinearity between the reaction variable and various illustrative factors, displaying the connection between the reaction variable and a few informative factors is troublesome.
Algamal, Zakariya Yahya, Hamad, Abed Ali
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A Modified New Two‐Parameter Estimator in a Linear Regression Model
Modelling and Simulation in Engineering, Volume 2019, Issue 1, 2019., 2019 The literature has shown that ordinary least squares estimator (OLSE) is not best when the explanatory variables are related, that is, when multicollinearity is present. This estimator becomes unstable and gives a misleading conclusion. In this study, a modified new two‐parameter estimator based on prior information for the vector of parameters is ...
Adewale F. Lukman +4 more
wiley +1 more source
, 2023 The negative binomial regression model (NBRM) is a generalized linear model which relaxes the restrictive assumption by the Poisson regression model when the variance is equal to the mean. The estimation of the parameters of the NBRM is obtained using the maximum likelihood (ML) method. Maximum likelihood estimator becomes unstable when the explanatory
Oranye Henrietta E +6 more
openaire +1 more source
Journal of Mathematics, Volume 2025, Issue 1, 2025.The negative binomial regression model (NBRM) is popular for modeling count data and addressing overdispersion issues. Generally, the maximum likelihood estimator (MLE) is used to estimate the NBRM coefficients. However, when the explanatory variables in the NBRM are correlated, the MLE yields inaccurate estimates.
Bushra Ashraf +5 more
wiley +1 more source
Data 20102021 ISBN LUKMAN YUDHO PRAKOSO
, 2021 20102021 ISBN LUKMAN YUDHO ...
Lukman Prakoso (11513074)
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Citation Reference Of Lukman Yudho Prakoso
, 2021 all data publication of Lukman ...
Lukman Yudho Prakoso (11572385)
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Generalized Kibria-Lukman Prediction Approximation in Linear Mixed Models
One of the new suggested prediction method is the Kibria-Lukman's prediction approach under multicollinearity in linear mixed models and in this article, the generalized Kibria-Lukman estimator and predictor are introduced to combat multicollinearity ...
Kuran, Özge
core +2 more sources
Research in StatisticsIn the presence of multicollinearity and outliers, the ordinary least squares (OLS) estimator becomes unstable. In addition, existing ridge and robust ridge estimators tend to become ineffective when there is significant contamination.
Danish Wasim +3 more
doaj +1 more source
Robust adaptive Kibria-Lukman estimator for COM-Poisson regression
Информатика. Экономика. УправлениеThe COM-Poisson regression model is a flexible model for count data that can be overdispersed and underdispersed. However, multicollinearity and contaminated observations can significantly increase estimation variability and reduce the reliability of ...
Ахмед Назих Аль-Хатиб
doaj +1 more source