The week's pick
Reseach Article
On the Application of Three-Term Conjugate Gradient Method in Regression Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 102 - Number 8 |
| Year of Publication: 2014 |
| Authors: Aliyu Usman Moyi, Wah June Leong, Ibrahim Saidu |
10.5120/17832-8517
|
Aliyu Usman Moyi, Wah June Leong, Ibrahim Saidu . On the Application of Three-Term Conjugate Gradient Method in Regression Analysis. International Journal of Computer Applications. 102, 8 ( September 2014), 1-4. DOI=10.5120/17832-8517
Abstract
Conjugate gradient methods have played a useful and powerful role for solving large-scale optimization problems which has become more interesting and essential in many disciplines such as in engineering, statistics, physical sciences, social and behavioral sciences among others. In this paper, we present an application of a proposed three-term conjugate gradient method in regression analysis. Numerical experiments show that the proposed method is promising and superior to many well-known conjugate gradient methods in terms of efficiency and robustness.
References
- Bates, D. M. and Watts,D. g. (1988). Non linear regeression analysis and its applications. New York, John Wiley & Sons
- Chatterjee, M. and Machler, M. (1997). Robust regression: A weighted least squares approach Communications in Statistics-Theory and Methods 26: 1381–1394.
- Christensen, R. (1996). Analysis of variance, design and regression: Applied Statistical Methods New York, Chapman and Hall.
- Gilbert, J. C. and Nocedal, J. (1992). Global convergence properties of conjugate gradient methods for optimization. SIAM Journal on Optimization 2 (1): 21–42.
- Hager,W. W. and Zhang, H. (2005). A new conjugate gradient method with guaranteed descent and an efficient line search. SIAM Journal on Optimization 16 (1): 170–192.
- Hestenes, M. R. and Stiefel, E. (1952). Methods of conjugate gradients for solving linear systems. Journal of Research of the National Bureau of Standards, 49: 409-436.
- Perry, J. M. (1977). A class of conjugate gradient algorithms with a two step variable metric memory. Center for Mathematical Studies in Economies and Management Science. Evanston Illiois: Northwestern University Press .
- Yuan, G. and Wei, Z. (2009). New line search methods for unconstrained optimization. Journal of the Korean Statistical Society 38 (1): 29–39.
- Yuan, G. and Wei, Z. (2013). Non Monotone Backtracking Inexact BFGS Method for Regression Analysis. Communications in Statistics-Theory and Methods 42 (2): 214–238.
- Zhang, L. , Zhou, W. and Li, D. (2006) A descent modified Polak-Ribiere-Polyak conjugate gradient method and its global convergence. IMA Journal of Numerical Analysis 26 (4): 629–640.
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