In this article, we proposed a new estimator namely, modified jackknifed generalized Liu-type estimator (MJGLE). It is based on the criterion that it combines the ideas underlying both the generalized Liu estimator (GLE) and jackknifed generalized Liu estimator (JGLE). The performance of this estimator (MJGLE) is compared to that of the GLE and the JGLE. The ideas in the article are illustrated and evaluated using a real data example and simulations. © 2010 Springer-Verlag
In regression analysis, ridge regression estimators and Liu type estimators are often used to overco...
Ordinary and jack-knifed ridge type estimators are compared for different measures of goodness. Alth...
Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper pr...
In this study, we proposed an alternative biased estimator. The linear regression model might lead t...
In 2003, Liu proposed a new estimator dealing with the problem of multicollinearity in linear regre...
The technique of jackknife is applied to a general class of estimators. Considering a natural popula...
WOS: A1995RG21200008In this paper, we derive the almost unbiased generalized Liu estimator and exami...
ABSTRACT: The paper introduces two jackknife estimators of the signal. The mean square errors of the...
In this paper we consider the semiparametric regression model, y=Xß+f+?. Recently, Hu [11] proposed ...
Abstract. A common problem in multiple regression models is multicollinearity, which pro-duces undes...
In this paper, the delete-mj jackknife estimator is proposed. This estimator is based on samples obt...
In practice, sometimes the data can be divided into several blocks but only a few of the largest obs...
Includes bibliographical references.Many important estimators in statistics have the property that t...
In empirical economics, the generalized method of moments (GMM) is one of the most widely used metho...
In this article, and in a context of regularly varying tails, we analyze a generalization of the cla...
In regression analysis, ridge regression estimators and Liu type estimators are often used to overco...
Ordinary and jack-knifed ridge type estimators are compared for different measures of goodness. Alth...
Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper pr...
In this study, we proposed an alternative biased estimator. The linear regression model might lead t...
In 2003, Liu proposed a new estimator dealing with the problem of multicollinearity in linear regre...
The technique of jackknife is applied to a general class of estimators. Considering a natural popula...
WOS: A1995RG21200008In this paper, we derive the almost unbiased generalized Liu estimator and exami...
ABSTRACT: The paper introduces two jackknife estimators of the signal. The mean square errors of the...
In this paper we consider the semiparametric regression model, y=Xß+f+?. Recently, Hu [11] proposed ...
Abstract. A common problem in multiple regression models is multicollinearity, which pro-duces undes...
In this paper, the delete-mj jackknife estimator is proposed. This estimator is based on samples obt...
In practice, sometimes the data can be divided into several blocks but only a few of the largest obs...
Includes bibliographical references.Many important estimators in statistics have the property that t...
In empirical economics, the generalized method of moments (GMM) is one of the most widely used metho...
In this article, and in a context of regularly varying tails, we analyze a generalization of the cla...
In regression analysis, ridge regression estimators and Liu type estimators are often used to overco...
Ordinary and jack-knifed ridge type estimators are compared for different measures of goodness. Alth...
Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper pr...