Title :
The Relative Efficiencies of the Parameter Estimate in Seemingly Unrelated Regression Models
Author :
Liu Haisheng ; Liu Meiling
Author_Institution :
China Inst. of Sci. & Technol., Beijing, China
Abstract :
For the regression system composed of the two linear regression equations, we propose three kinds of relative efficiencies of the covariance improvement on the unknown parameter vector toward the best linear unbiased estimate, the lower bounds of which are respectively given in the paper. Then the three kinds of efficiencies are compared by numerical simulation so that the best are found.
Keywords :
parameter estimation; regression analysis; best linear unbiased estimate; linear regression equations; lower bounds; numerical simulation; parameter estimate; regression system; seemingly unrelated regression models; unknown parameter vector; Biological system modeling; Estimation; Loss measurement; Mathematical model; Numerical models; Symmetric matrices; Vectors; Closed-loop control; Reactive power compensation; Single-phase photovoltaic inverter;
Conference_Titel :
Intelligent Systems Design and Engineering Applications, 2013 Fourth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-2791-3
DOI :
10.1109/ISDEA.2013.565
