Results 41 to 50 of about 163,142 (181)

A Modified New Two-Parameter Estimator in a Linear Regression Model

Modelling and Simulation in Engineering, 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.
Adewale F. Lukman, Kayode Ayinde, Sek Siok Kun, Emmanuel T. Adewuyi   +3 more
doaj   +1 more source

Inference for High-dimensional Differential Correlation Matrices [PDF]

, 2015
Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices.
Cai, T. Tony, Zhang, Anru
core   +3 more sources

New estimators for the probit regression model with multicollinearity

Scientific African, 2023
The probit regression model (PRORM) aims to model a binary response with one or more explanatory variables. The parameter of the PRORM is estimated using an estimation method called the maximum likelihood (ML), like a logistic model.
Mohamed R. Abonazel, Issam Dawoud, Fuad A. Awwad, Elsayed Tag-Eldin   +3 more
doaj   +1 more source

A New Conway Maxwell–Poisson Liu Regression Estimator—Method and Application

Journal of Mathematics, 2022
Poisson regression is a popular tool for modeling count data and is applied in medical sciences, engineering and others. Real data, however, are often over or underdispersed, and we cannot apply the Poisson regression. To overcome this issue, we consider
Muhammad Nauman Akram, Muhammad Amin, Faiza Sami, Adam Braima Mastor, Omer Mohamed Egeh, Abdisalam Hassan Muse   +5 more
doaj   +1 more source

Generalized Kibria-Lukman Estimator: Method, Simulation, and Application

Frontiers in Applied Mathematics and Statistics, 2022
In the linear regression model, the multicollinearity effects on the ordinary least squares (OLS) estimator performance make it inefficient. To solve this, several estimators are given. The Kibria-Lukman (KL) estimator is a recent estimator that has been
Issam Dawoud, Mohamed R. Abonazel, Fuad A. Awwad   +2 more
doaj   +1 more source

A New Biased Estimation Class to Combat the Multicollinearity in Regression Models: Modified Two--Parameter Liu Estimator

Computational Journal of Mathematical and Statistical Sciences
The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by many authors.
Mohamed Reda Abonazel
doaj   +1 more source

Modified Liu estimator to address the multicollinearity problem in regression models: A new biased estimation class

Scientific African, 2022
The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by lots of authors.
Issam Dawoud, Mohamed R. Abonazel, Fuad A. Awwad   +2 more
doaj   +1 more source

New Robust Estimators for Handling Multicollinearity and Outliers in the Poisson Model: Methods, Simulation and Applications

Axioms, 2022
The Poisson maximum likelihood (PML) is used to estimate the coefficients of the Poisson regression model (PRM). Since the resulting estimators are sensitive to outliers, different studies have provided robust Poisson regression estimators to alleviate ...
Issam Dawoud, Fuad A. Awwad, Elsayed Tag Eldin, Mohamed R. Abonazel   +3 more
doaj   +1 more source

Liu Estimation Method in the Zero-Inflated Conway Maxwell Poisson Regression Model

Journal of Statistical Theory and Applications (JSTA)
The Zero-Inflated Conway-Maxwell Poisson Regression Model (ZICPRM) is developed specifically for overdispersed, underdispersed, and excessive zeros in the count data. The ZICMPRM is estimated by the maximum likelihood estimator (MLE).
Muhammad Amin, Bushra Ashraf, Syeda Maryam Siddiqa   +2 more
doaj   +1 more source

Kibria-Lukman Estimator for General Linear Regression Model with AR(2) Errors: A Comparative Study with Monte Carlo Simulation

Journal of New Theory, 2022
The sensitivity of the least-squares estimation in a regression model is impacted by multicollinearity and autocorrelation problems. To deal with the multicollinearity, Ridge, Liu, and Ridge-type biased estimators have been presented in the statistical ...
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doaj   +1 more source