Results 211 to 220 of about 123,927 (254)
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Using Liu-Type Estimator to Combat Collinearity
Communications in Statistics - Theory and Methods, 2003Linear regression model and least squares method are widely used in many fields of natural and social sciences. In the presence of collinearity, the least squares estimator is unstable and often gives misleading information. Ridge regression is the most common method to overcome this problem.
Kejian Liu
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A new Liu-type estimator in linear regression model
Statistical Papers, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yalian Li, Hu Yang
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Robust Liu‐type estimator based on GM estimator
Statistica Neerlandica, 2023Ordinary Least Squares Estimator (OLSE) is widely used to estimate parameters in regression analysis. In practice, the assumptions of regression analysis are often not met. The most common problems that break these assumptions are outliers and multicollinearity problems. As a result of these problems, OLSE loses efficiency.
Melike Işılar, Y. Murat Bulut
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Inverse Gaussian Liu-type estimator
Communications in Statistics - Simulation and Computation, 2021The inverse Gaussian regression (IGR) model parameters are generally estimated using the maximum likelihood (ML) estimation method.
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Liu-type estimator for the gamma regression model
Communications in Statistics - Simulation and Computation, 2018In this paper, we propose a new biased estimator called Liu-type estimator in gamma regression models in the presence of collinearity.
Zakariya Yahya Algamal, Yasin Asar
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Evaluation of the predictive performance of the Liu type estimator
Communications in Statistics - Simulation and Computation, 2016Multiple linear regression models are frequently used in predicting (forecasting) unknown values of the response variable y. In this case, a regression model ability to produce an adequate prediction equation is of prime importance. This paper discusses the predictive performance of the Liu estimator compared to ordinary least squares, as well as to ...
Dawoud I., Kaçiranlar S.
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Robust Liu-type estimator for regression based on M-estimator
Communications in Statistics - Simulation and Computation, 2015ABSTRACTThe problem of multicollinearity and outliers in the dataset can strongly distort ordinary least-square estimates and lead to unreliable results. We propose a new Robust Liu-type M-estimator to cope with this combined problem of multicollinearity and outliers in the y-direction.
Hasan Ertas +2 more
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Developing a
AbstractThe beta regression model is a commonly used when the response variable has the form of fractions or percentages. The maximum likelihood (ML) estimator is used to estimate the regression coefficients of this model. However, it is known that multicollinearity problem affects badly the variance of ML estimator.
Zakariya Yahya Algamal +1 more
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On the Principal Component Liu-type Estimator in Linear Regression
Communications in Statistics - Simulation and Computation, 2014In this article, we present a principal component Liu-type estimator (LTE) by combining the principal component regression (PCR) and LTE to deal with the multicollinearity problem. The superiority of the new estimator over the PCR estimator, the ordinary least squares estimator (OLSE) and the LTE are studied under the mean squared error matrix.
Jibo Wu, Hu Yang 0001
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Liu-type Estimator in the Bell Regression Model
2022This study proposes a new estimator used in the case of multicollinearity problems in the Bell regression model that is an alternative model for the Poissonregression model. The Bell regression model is used to solve the overdispersion problem. Generally, the maximum likelihood estimation (MLE) method is used toestimate the parameters of the Bell ...
IŞILAR, Melike, BULUT, Y. Murat
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