The estimation of ridge parameter is an important problem in the ridge regression method, which is widely used to solve multicollinearity problem. A comprehensive study on 28 different available estimators and five proposed ridge estimators, KB1, KB2, KB3, KB4, and KB5, is provided. A simulation study was conducted and selected estimators were compared. Some of selected ridge estimators performed well compared to the ordinary least square (OLS) estimator and some existing popular ridge estimators. One of the proposed estimators, KB3, performed the best. Numerical examples were given
The problem of multicollinearity is often encountered in time series data since explanato...
Ridge regression techniques have been extensively used to solve the multicollinearity problem for bo...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
In this paper we review some existing and propose some new estimators for estimating the ridge param...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary ...
AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the...
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
Different methodshave been adopted in the estimation of ridge parameter in ordinary ridge regressio...
AbstractRidge regression estimator has been introduced as an alternative to the ordinary least squar...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
The problem of multicollinearity is often encountered in time series data since explanato...
Ridge regression techniques have been extensively used to solve the multicollinearity problem for bo...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
In this paper we review some existing and propose some new estimators for estimating the ridge param...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary ...
AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the...
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
Different methodshave been adopted in the estimation of ridge parameter in ordinary ridge regressio...
AbstractRidge regression estimator has been introduced as an alternative to the ordinary least squar...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
The problem of multicollinearity is often encountered in time series data since explanato...
Ridge regression techniques have been extensively used to solve the multicollinearity problem for bo...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...