**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:**

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

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

**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.