Results 21 to 30 of about 19,774 (283)
A new Liu-type estimator in a mixed Poisson regression model [PDF]
Mixed Poisson regression models (MPRMs) are widely used for analyzing overdispersed count data. However, the presence of multicollinearity among explanatory variables poses challenges when estimating regression coefficients using the maximum likelihood ...
Ohud A. Alqasem +4 more
doaj +2 more sources
A New Liu Type of Estimator for the Restricted SUR Estimator
A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived.
Kristofer Månsson +2 more
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Estimation methods of logistic regression in context of multicollinearity (Comparative study) [PDF]
The binary logistic regression (BLR) model is used as an alternative to the commonly used linear regression model when the response variable is binary.
Hassan Mohamed Ali +2 more
doaj +1 more source
The Conway–Maxwell–Poisson (COMP) model is defined as a flexible count regression model used for over- and under-dispersion cases. In regression analysis, when the explanatory variables are highly correlated, this means that there is a multicollinearity ...
Mohamed R. Abonazel +4 more
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A New Two-Parameter Estimator for Beta Regression Model: Method, Simulation, and Application
The beta regression is a widely known statistical model when the response (or the dependent) variable has the form of fractions or percentages. In most of the situations in beta regression, the explanatory variables are related to each other which is ...
Mohamed R. Abonazel +3 more
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On a Mixed Poisson Liu Regression Estimator for Overdispersed and Multicollinear Count Data
The mixed Poisson regression models are commonly employed to analyze the overdispersed count data. However, multicollinearity is a common issue when estimating the regression coefficients by using the maximum likelihood estimator (MLE) in such regression
Ramajeyam Tharshan +1 more
doaj +1 more source
On Liu estimators for the logit regression model [PDF]
This paper introduces a shrinkage estimator for the logit model which is a generalization of the estimator proposed by Liu (1993) for the linear regression. This new estimation method is suggested since the mean squared error (MSE) of the commonly used maximum likelihood (ML) method becomes inflated when the explanatory variables of the regression ...
Månsson, Kristofer +2 more
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Liu-type shrinkage estimations in linear models
In this study, we present the preliminary test, Stein-type and positive part Liu estimators in the linear models when the parameter vector $\boldsymbolβ$ is partitioned into two parts, namely, the main effects $\boldsymbolβ_1$ and the nuisance effects $\boldsymbolβ_2$ such that $\boldsymbolβ=\left(\boldsymbolβ_1, \boldsymbolβ_2 \right)$.
Bahadır Yüzbaşı +2 more
openaire +2 more sources
A new biased regression estimator: Theory, simulation and application
The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud +2 more
doaj +1 more source
Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear model. Alternative estimators to the MLE include the ridge estimator, the Liu estimator and the
Olukayode Adebimpe +4 more
doaj +1 more source

