Results 211 to 220 of about 123,927 (253)

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

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
openaire   +1 more source

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-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
openaire   +1 more source

More on Liu-Type Estimator in Linear Regression

Communications in Statistics - Theory and Methods, 2004
Abstract Recently, Liu [Liu, K. (2003). Using Liu-type estimator to combat collinearity. Commun. Statist. Theory Methods 32:1009–1020] introduced the Liu-type estimator to combat collinearity in linear regression. The Liu-type estimator can be applied in two ways. First, when the effect of collinearity is moderate, the Liu-type estimator can be used as
Kejian Liu
exaly   +2 more sources

Using Liu-Type Estimator to Combat Collinearity

Communications in Statistics - Theory and Methods, 2003
Linear 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
exaly   +2 more sources

Developing a Liu‐type estimator in beta regression model

Concurrency and Computation: Practice and Experience, 2021
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, Mohamed Reda Abonazel   +1 more
openaire   +1 more source

On the Principal Component Liu-type Estimator in Linear Regression

Communications in Statistics - Simulation and Computation, 2014
In 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
openaire   +1 more source

Liu-type Estimator in the Bell Regression Model

2022
This 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
openaire   +2 more sources

New Shrinkage Parameters for the Liu-type Logistic Estimators

Communications in Statistics - Simulation and Computation, 2015
The binary logistic regression is a widely used statistical method when the dependent variable has two categories. In most of the situations of logistic regression, independent variables are collinear which is called the multicollinearity problem. It is known that multicollinearity affects the variance of maximum likelihood estimator (MLE) negatively ...
Yasin Asar, Asir Genç
openaire   +2 more sources