A Revisit to the Application of Weighted Mixed Regression Estimation in Linear Regression Models with Missing Data

Toutenburg, Helge and Srivastava, V. K. (2001): A Revisit to the Application of Weighted Mixed Regression Estimation in Linear Regression Models with Missing Data. Collaborative Research Center 386, Discussion Paper 241

Abstract

This paper deals with the application of the weighted mixed regression estimation of the coefficients in a linear model when some values of some of the regressors are missing. Taking the weight factor as an arbitrary scalar, the performance of weighted mixed regression estimator in relation to the conventional least squares and mixed regression estimators is analyzed and the choice of scalar is discussed. Then taking the weight factor as a specific matrix, a family of estimators is proposed and its performance properties under the criteria of bias vector and mean squared error matrix are analyzed.

• Item Type: Paper
• Faculties: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English