Results 11 to 20 of about 163,142 (181)
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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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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Liu-type shrinkage estimations in linear models
Statistics, 2022 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
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A new biased regression estimator: Theory, simulation and application
Scientific African, 2022 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
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Statistical Papers, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kurnaz, Fatma Sevinc, Akay, Kadri Ulas
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On Liu estimators for the logit regression model [PDF]
Economic Modelling, 2012 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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Efficiency of the Principal Component Liu-Type Estimator in Logistic Regression
Revstat Statistical Journal, 2020 In this paper we propose a principal component Liu-type logistic estimator by combining the principal component logistic regression estimator and Liu-type logistic estimator to overcome the multicollinearity problem. The superiority of the new estimator
Jibo Wu , Yasin Asar
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F1000Research, 2021 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
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Large Covariance Estimation by Thresholding Principal Orthogonal Complements [PDF]
, 2013 This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-
Fan, Jianqing +2 more
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On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion
Journal of Applied Mathematics, 2013 Wu (2013) proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity. This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu ...
Jibo Wu
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