Add to ORKGRidge Regression and Robust Regression Estimators were proposed to deal with the problem of multicollinearity and outlier in a classical linear regression model respectively. This paper proposes a robust ridge regression estimator (RRR) for solving the problem of multicollinearity and outlier in a classical linear regression model simultaneously
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
The ordinary least-square estimators for linear regression analysis with multicollinearity and outli...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...
Common problems in multiple linear regression models are multicollinearity and outliers. In this pap...
Two Stage Robust Ridge Estimators based on robust estimators M, MM, S, LTS are examined in the prese...
In multiple linear regression analysis, multicollinearity and outliers are two main problems. When m...
Robust ridge methods based on M, S, MM and GM estimators are examined in the presence of multicollin...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
This paper introduces a new estimator, of ridge parameter k for ridge regression and then evaluated ...
The estimation of ridge parameter is an important problem in the ridge regression method, which is w...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
The ridge estimator for handling multicollinearity problem in linear regression model requires the ...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary ...
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
The ordinary least-square estimators for linear regression analysis with multicollinearity and outli...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...
Common problems in multiple linear regression models are multicollinearity and outliers. In this pap...
Two Stage Robust Ridge Estimators based on robust estimators M, MM, S, LTS are examined in the prese...
In multiple linear regression analysis, multicollinearity and outliers are two main problems. When m...
Robust ridge methods based on M, S, MM and GM estimators are examined in the presence of multicollin...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
This paper introduces a new estimator, of ridge parameter k for ridge regression and then evaluated ...
The estimation of ridge parameter is an important problem in the ridge regression method, which is w...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
The ridge estimator for handling multicollinearity problem in linear regression model requires the ...
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been pr...
Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary ...
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
The ordinary least-square estimators for linear regression analysis with multicollinearity and outli...
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importan...