Abstract. In this paper, a new ridge-type estimator is proposed and termed as the new mixed ridge estimator (NMRE) which is obtained by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) with respect to the ME are examined under the criterion of mean squared error matrix. Finally, a numerical example and a Monte Carlo simulation are also presented to analyze.

No abstract

In this paper, we introduce the mixed ridge estimator (MRE) in linear measurement error models with stochastic linear restrictions and present the method of weighted mixed ridge estimation, which permits to assign possibly unequal weights to the prior information in relation to the sample information. The performance of the weighted mixed ridge estimator (WMRE) against the weighted mixed estimator (WME) is examined in terms of the mean squared error matrix (MSEM) of estimators. Finally, a simulation study and a numerical example are also given to show the theoretical results.

No abstract

No abstract