Matrix theory: a second course
Matrix theory: a second course
Principles of multivariate analysis: a user's perspective
Principles of multivariate analysis: a user's perspective
The projected gradient methods for least squares matrix approximations with spectral constraints
SIAM Journal on Numerical Analysis
SIAM Journal on Scientific Computing
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
On a differential equation approach to the weighted orthogonal Procrustes problem
Statistics and Computing
A maximum likelihood method for an asymmetric MDS model
Computational Statistics & Data Analysis
Advances in Data Analysis and Classification
Hi-index | 0.00 |
A model for analysis and visualization of asymmetric data—GIPSCAL—is reconsidered by means of the projected gradient approach. GIPSCAL problem is formulated as initial value problem for certain first order matrix ordinary differential equations. This results in a globally convergent algorithm for solving GIPSCAL. Additionally, first and second order optimality conditions for the solutions are established. A generalization of the GIPSCAL model for analyzing three-way arrays is also considered. Finally, results from simulation experiments are reported.