Results 241 to 250 of about 164,145 (281)

On the Restricted Liu Estimator in the Logistic Regression Model

Communications in Statistics - Simulation and Computation, 2014
The logistic regression model is used when the response variables are dichotomous. In the presence of multicollinearity, the variance of the maximum likelihood estimator (MLE) becomes inflated. The Liu estimator for the linear regression model is proposed by Liu to remedy this problem. Urgan and Tez and Mansson et al.
Gülesen Üstündag Siray, Selma Toker, Selahattin Kaçiranlar   +2 more
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Weighted ridge and Liu estimators for linear regression model

Concurrency and Computation: Practice and Experience, 2022
SummaryIn linear regression model, ridge regression and two‐parameter Liu estimator (LE) are the most widely used methods in recent decade to overcome the problem of multicollinearity especially for ill conditioned cases. In this article, we propose new weighted ridge and Liu estimators which remain positive for each level of multicollinearity and also
Iqra Babar, Sohail Chand
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Robust Liu-type estimator for regression based on M-estimator

Communications in Statistics - Simulation and Computation, 2015
ABSTRACTThe 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, Selahattin Kaçiranlar, Hüseyin Güler   +2 more
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Liu-type estimator for the gamma regression model

Communications in Statistics - Simulation and Computation, 2018
In 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, 2016
Multiple 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 estimator for regression based on an M-estimator

Journal of Applied Statistics, 2000
Consider the regression model y = beta 0 1 + Xbeta + epsilon. Recently, the Liu estimator, which is an alternative biased estimator beta L (d) = (X'X + I) -1 (X'X + dI)beta OLS , where ...
Arslan O., Billor N.
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Two Stages Liu Regression Estimator

Communications in Statistics - Simulation and Computation, 2015
This paper introduces a new estimator for multicollinearity and autocorrelated errors. We propose the Two Stages Liu estimator (TL) for the multiple linear regression model which suffers from autocorrelation AR(1) and multicollinearity problems. We use a mixed method to apply the two stages least squares procedure (TS) for deriving the TL estimator. We
Issam Dawoud, Selahattin Kaçiranlar
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On the Stein-Type Liu Estimator and Positive-Rule Stein-Type Liu Estimator in Multiple Linear Regression Models

Communications in Statistics - Theory and Methods, 2012
In this article, the Stein-type Liu estimator and positive-rule Stein-type Liu estimator are constructed for the parameter vector in a multiple linear model under a multicollinearity situation when it is suspected that the regression coefficients may be restricted to a subspace.
Hu Yang
exaly   +2 more sources

A state estimation of Liu equations

AIP Conference Proceedings, 2015
This paper is concerned with state estimation problems for so-called Liu equations. These equations are counterparts of well-known Ito ones and they were introduced by B. Liu under elaboration of his uncertain theory. The Liu equations may be solved backward and they represent a more convenient object for the state estimation problem solution ...
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Evaluation of the Predictive Performance of the Liu Estimator

Communications in Statistics - Theory and Methods, 2013
Multiple 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 ...
Özbey F., Kaçiranlar S.
openaire   +2 more sources