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Logistic Liu Estimator under stochastic linear restrictions

Statistical Papers, 2016
The general logistic regression model is considered. The following stochastic prior information is given $h=H\beta+v$, $E(v)=0$. Here $h$ is a known vector, $H$ is a full rank known matrix, $\beta$ is a vector of regression coefficients to be estimated, and $v$ is a random vector of disturbances with known positive definite variance-covariance matrix ...
Nagarajah Varathan   +1 more
openaire   +1 more source

Modified almost unbiased Liu estimator in logistic regression

Communications in Statistics - Simulation and Computation, 2019
This paper focuses on introducing a new parameter estimator to the logistic regression model when the multicollinearity presents.
Nagarajah Varathan   +1 more
openaire   +1 more source

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   +3 more sources

Adjustive Liu-Type Estimators in Linear Regression Models

Communications in Statistics - Simulation and Computation, 2010
In this article, we aim to put forward the notion of adjustive Liu-type estimator (ALTE) in the linear regression model. First, the explicit expression of the optimal selection of the adjustive factors is derived under the PRESS criterion through matrix techniques. Then, the results are applied to the dataset on Portland cement.
openaire   +2 more sources

A New Liu-Ratio Estimator For Linear Regression Models

Istanbul Journal of Mathematics
Summary: In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable and one or more independent variables. Although there are various methods for estimating parameters, the most popular is the Ordinary Least Squares (OLS) method.
Giresunlu, İ. M.   +2 more
openaire   +2 more sources

Modified restricted Liu estimator in logistic regression model

Computational Statistics, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources

Improved Liu-type estimator in partial linear model

International Journal of Computer Mathematics, 2015
In this article, a Liu-type estimation is proposed for the vector-parameter in a partial linear model. This new estimator can be regarded as generalization of the restricted least-squares estimator, the restricted ridge estimator and the restricted Liu estimator. We also obtain the asymptotic distributional bias and risk of these estimators and we also
openaire   +1 more source

MODIFICATION OF LIU-TYPE ESTIMATOR FOR TWO SUR MODEL

Advances and Applications in Statistics, 2019
Summary: In this paper, we suggest a new biased Liu-Type estimator for the vector of parameters in a two SUR model. This Liu-type two SUR estimator based on ridge estimation. Furthermore, the superiority of this estimator from the ridge estimator and Liu-Type estimator was verified by mean square error (MSE).
openaire   +1 more source

Developing a Liu-type estimator in beta regression model

Concurrency Computation Practice and Experience, 2022
Mohamed R Abonazel   +1 more
exaly  

Liu-type estimator for the gamma regression model

Communications in Statistics Part B: Simulation and Computation, 2020
Zakariya Yahya Algamal, Yasin Asar
exaly  

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