Results 221 to 230 of about 123,209 (248)
Some of the next articles are maybe not open access.
Generalized Liu Type Estimators Under Zellner's Balanced Loss Function
Communications in Statistics - Theory and Methods, 2005ABSTRACT In regression analysis, ridge regression estimators and Liu type estimators are often used to overcome the problem of multicollinearity. These estimators have been evaluated using the risk under quadratic loss criterion, which places sole emphasis on estimators′ precision. The traditional mean square error (MSE) as the measure of efficiency of
Akdeniz F., Wan A.T.K., Akdeniz E.
openaire +1 more source
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.
Ertaş H., Kaçıranlar S., Güler H.
openaire +1 more source
Almost unbiased Liu-type estimators in gamma regression model
Journal of Computational and Applied Mathematics, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yasin Asar, Merve Korkmaz
openaire +2 more sources
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
openaire +1 more source
MODIFICATION OF LIU-TYPE ESTIMATOR FOR TWO SUR MODEL
Advances and Applications in Statistics, 2019Summary: 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
On Liu-type biased estimators in measurement error models
Statistics, 2020This paper considers the shrinkage estimation of parameters of measurement error models when it is suspected that the parameters may belong to a linear subspace.
A. K. Md. Ehsanes Saleh, null Shalabh
openaire +1 more source
Improved Liu-type estimator in partial linear model
International Journal of Computer Mathematics, 2015In 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
Liu-type estimator in semiparametric partially linear additive models
Journal of Nonparametric Statistics, 2016Partially linear additive model is useful in statistical modelling as a multivariate nonparametric fitting technique. This paper considers statistical inference for the semiparametric model in the presence of multicollinearity. Based on the profile least-squares (PL) approach and Liu estimation method, we propose a PL Liu estimator for the parametric ...
Chuanhua Wei, Xiaonan Wang
openaire +1 more source
Adjustive Liu-Type Estimators in Linear Regression Models
Communications in Statistics - Simulation and Computation, 2010In 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 +1 more source
New Shrinkage Parameters for the Liu-type Logistic Estimators
Communications in Statistics - Simulation and Computation, 2015The 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 ...
Asar, Yasin, Genc, Asir
openaire +2 more sources

