The Generalized New Two-Type ParameterEstimator in Linear Regression Model

In this paper, a new two-type parameter estimator is proposed. This estimator is ageneralization of the new two parameter (NTP) estimator introduced by Yang and Chang[8], which includes the ordinary least squares (OLS), the generalized ridge (GR) andgeneralized Liu (GL) estimators, as special cases. Here, the performance of this newestimator is, theoretically, investigated over the OLS, the GR, the GL and the NTPestimators in terms of mean squared error matrix (MSEM) criterion. Furthermore, theestimation of the biasing parameters is obtained to minimize the scalar mean squared error(MSE). In addition, a complementary algorithm is proposed for the estimator presented byYang and Chang [8]. As well, a numerical example is given and a simulation study is done

The Generalized New Two-Type ParameterEstimator in Linear Regression Model Keywords:

Generalized Liu estimator , Generalized Ridgeestimator , Lagrangemethod , Mean squarederror , Two-parameterestimator.