Mixed Liu estimator in linear measurement error models

The Mixed Liu Estimator in Stochastic Restricted Linear Measurement Error Model

“…In order to deal with the collinearity problem, Ghapani and Babdi [1] introduced a Liu estimator (LE), and this estimator can be obtained as follows: based on (3), consider the following objective function:…”

“…In the linear measurement error model, the collinearity problem may also lead the estimator unstable. In order to deal with this problem, Saleh and Shalabh [11] considered the ridge estimator and Ghapani and Babdi [1] considered the Liu estimator. When the linear restrictions or stochastic linear restrictions are satisfied in linear measurement error model, Li et al [12] proposed some new estimators and discussed the properties of these estimators under Pitman's closeness criterion.…”

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Ghapani and Babdi [1] proposed a mixed Liu estimator in linear measurement error model with stochastic linear restrictions. In this article, we propose an alternative mixed Liu estimator in the linear measurement error model with stochastic linear restrictions.

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“…In this article, we propose an alternative mixed Liu estimator in the linear measurement error model with stochastic linear restrictions. e performance of the new mixed Liu estimator over the mixed estimator, Liu estimator, and mixed Liu estimator proposed by Ghapani and Babdi [1] are discussed in the sense of mean squared error matrix. Finally, a simulation study is given to show the performance of these estimators.…”