Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30127
The New Relative Efficiency Based on the Least Eigenvalue in Generalized Linear Model

Authors: Chao Yuan, Bao Guang Tian

Abstract:

A new relative efficiency is defined as LSE and BLUE in the generalized linear model. The relative efficiency is based on the ratio of the least eigenvalues. In this paper, we discuss about its lower bound and the relationship between it and generalized relative coefficient. Finally, this paper proves that the new estimation is better under Stein function and special condition in some degree.

Keywords: Generalized linear model, generalized relative coefficient, least eigenvalue, relative efficiency.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339390

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 833

References:


[1] A.Y. Liu, S.G. Wang. A new relative efficiency of least square estimation in linear model. Applied probability and statistics, 1989, 15(2), pp.97-104.
[2] Rao. C.R. Least squares theory using an estimated dispersion matrix and its application to measurement of signals,In Proceedings of the Fifth Berkeley Symposium on Math. Statist &Pro.Eds.by Lecam, J and Neyman, J . Vol.1.1967.
[3] Knott On the Minimum efficiency of least Squaces.Biometrika,1975,62, pp.129-132.
[4] Y.L. Huan, G.J. Chen. The relative efficiency of parameter estimation in linear model. Applied probability and statistics, 1998, 14(2), pp.159-164.
[5] S.G. Wang, M.X. Wu, Z.Z. Jia. Matrix inequality. Beijing Science Press,2006.
[6] R.T. Zhang, K.T. Fang. An introduction to multivariate statistical analysis. Beijing Science Press,1999.
[7] A.J. Shi. Relative efficiency based on the minimum eigenvalue. Journal of Nanjing University of Posts and Telecommunications, 2007, 27(2),pp.76-79.