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Liu -Type Estimator and Selection of Variables [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2012 In this paper we consider the generalized Liu-type estimator and combine it into subset selection criterion using Cp statistic. Our proposed method can be derived via natural extension of two well-known techniques: one is shrinkage estimators and the ...
Mustafa Ismaeel. Niaf
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On the Liu and almost unbiased Liu estimators in the presence of multicollinearity with heteroscedastic or correlated errors [PDF]
Surveys in Mathematics and its Applications, 2009 This paper introduces a new biased estimator, namely, almost unbiased Liu estimator (AULE) of β for the multiple linear regression model with heteroscedastics and/or correlated errors and suffers from the problem of multicollinearity.
Mustafa I. Alheety, B. M. Golam Kibria
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A new Liu-type estimator in a mixed Poisson regression model [PDF]
Scientific ReportsMixed 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
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Superiority of the Stochastic Restricted Liu Estimator under misspecification
Statistica, 2007 This paper deals with the use of correct prior infromation in the estimation of regression coefficients when the regression model is misspecified due to the exclusion of some relevant regressor variables.
M. H. Hubert, Pushba Wijekoon
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New Restricted Liu Estimator in a Partially Linear Model
Discrete Dynamics in Nature and Society, 2020 In this paper, we introduce a new restricted Liu estimator in a partially linear model when addition linear constraints are assumed to hold. We also consider the asymptotic normality of the new estimator.
Jibo Wu, Yong Li
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Estimation methods of logistic regression in context of multicollinearity (Comparative study) [PDF]
Maǧallaẗ Al-Buḥūṯ Al-Tiǧāriyyaẗ, 2023 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
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Frontiers in Applied Mathematics and Statistics, 2023 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
Frontiers in Applied Mathematics and Statistics, 2022 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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The Mixed Liu Estimator in Stochastic Restricted Linear Measurement Error Model
Journal of Mathematics, 2021 Ghapani and Babdi [1] proposed a mixed Liu estimator in linear measurement error model with stochastic linear restrictions. In this article, we propose an alternative mixed Liu estimator in the linear measurement error model with stochastic linear ...
Jibo Wu
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On a Mixed Poisson Liu Regression Estimator for Overdispersed and Multicollinear Count Data
The Scientific World Journal, 2022 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
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