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                                       Details van artikel 6 van 20 gevonden artikelen
 
 
  A new estimator combining the ridge regression and the restricted least squares methods of estimation
 
 
Titel: A new estimator combining the ridge regression and the restricted least squares methods of estimation
Auteur: Sarkar, Nityananda
Verschenen in: Communications in statistics
Paginering: Jaargang 21 (1992) nr. 7 pagina's 1987-2000
Jaar: 1992
Inhoud: It is well-known in the literature on multicollinearity that one of the major consequences of multicollinearity on the ordinary least squares estimator is that the estimator produces large sampling variances, which in turn might inappropriately lead to exclusion of otherwise significant coefficients from the model. To circumvent this problem, two accepted estimation procedures which are often suggested are the restricted least squares method and the ridge regression method. While the former leads to a reduction in the sampling variance of the estimator, the later ensures a smaller mean square error value for the estimator. In this paper we have proposed a new estimator which is based on a criterion that combines the ideas underlying these two estimators. The standard properties of this new estimator have been studied in the paper. It has also been shown that this estimator is superior to both the restricted least squares as well as the ordinary ridge regression estimators by the criterion of mean sauare error of the estimator of the regression coefficients when the restrictions are indeed correct. The conditions for superiority of this estimator over the other two have also been derived for the situation when the restrictions are not correct.
Uitgever: Taylor & Francis
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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