TY - JOUR
T1 - Block relaxation and majorization methods for the nearest correlation matrix with factor structure
AU - Li, Qingna
AU - Qi, Houduo
AU - Xiu, Naihua
PY - 2011/10
Y1 - 2011/10
N2 - We propose two numerical methods, namely the alternating block relaxation method and the alternating majorization method, for the problem of nearest correlation matrix with factor structure, which is highly nonconvex. In the block relaxation method, the subproblem is of the standard trust region problem, which is solved by Steighaugs truncated conjugate gradient method or by the exact trust region method. In the majorization method, the subproblem has a closed-form solution. We then apply the majorization method to the case where nonnegative factors are required. The numerical results confirm that the proposed methods work quite well and are competitive against the best available methods.
AB - We propose two numerical methods, namely the alternating block relaxation method and the alternating majorization method, for the problem of nearest correlation matrix with factor structure, which is highly nonconvex. In the block relaxation method, the subproblem is of the standard trust region problem, which is solved by Steighaugs truncated conjugate gradient method or by the exact trust region method. In the majorization method, the subproblem has a closed-form solution. We then apply the majorization method to the case where nonnegative factors are required. The numerical results confirm that the proposed methods work quite well and are competitive against the best available methods.
KW - Block relaxation methods
KW - Correlation matrix
KW - Factor structure
KW - Majorization methods
UR - http://www.scopus.com/inward/record.url?scp=80054936156&partnerID=8YFLogxK
U2 - 10.1007/s10589-010-9374-y
DO - 10.1007/s10589-010-9374-y
M3 - Article
AN - SCOPUS:80054936156
SN - 0926-6003
VL - 50
SP - 327
EP - 349
JO - Computational Optimization and Applications
JF - Computational Optimization and Applications
IS - 2
ER -