Methods of estimating the ridge parameter in ridge regression analysis are available in the literature. This paper proposed some methods based on the works of Lawless and Wang (1976) and Khalaf and Shurkur (2005). A simulation study was conducted and mean square error (MSE) criterion was used to compare the performances of the proposed estimators and some other existing ones. It was observed that the performance of the these estimators depend on the variance of the random error , the correlation among the explanatory variables , the sample size and the number of explanatory variables . The increase in the number of explanatory variables and increase in the sample size reduces the MSE of the estimators even when the correlation between ...
Ridge regression is used to circumvent the problem of multicollinearity among predictors and many es...
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates th...
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates th...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
In this paper we review some existing and propose some new estimators for estimating the ridge param...
The ridge estimation of the precision matrix is investigated in the setting where the number of vari...
AbstractRidge regression estimator has been introduced as an alternative to the ordinary least squar...
AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the...
ABSTRACTPresence of collinearity among the explanatory variables results in larger standard errors o...
Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinar...
In ordinary ridge regression, the estimation of the ridge parameter is a significant topic. This art...
Multiple linear regression is a widely used statistical method. Its application, especially in the s...
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
Includes bibliographical references (pages 51-53)In the standard regression technique, ordinary leas...
Ridge regression is used to circumvent the problem of multicollinearity among predictors and many es...
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates th...
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates th...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
In this paper we have reviewed some existing and proposed some new estimators for estimating the rid...
In this paper we review some existing and propose some new estimators for estimating the ridge param...
The ridge estimation of the precision matrix is investigated in the setting where the number of vari...
AbstractRidge regression estimator has been introduced as an alternative to the ordinary least squar...
AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the...
ABSTRACTPresence of collinearity among the explanatory variables results in larger standard errors o...
Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinar...
In ordinary ridge regression, the estimation of the ridge parameter is a significant topic. This art...
Multiple linear regression is a widely used statistical method. Its application, especially in the s...
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
Includes bibliographical references (pages 51-53)In the standard regression technique, ordinary leas...
Ridge regression is used to circumvent the problem of multicollinearity among predictors and many es...
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates th...
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates th...