Name
Title | ||
|---|---|---|
Maximum likelihood parameter and rank estimation in reduced-rank multivariate linear regressions |
Abstract | ||
|---|---|---|
This paper considers the problem of maximum likelihood (ML) estimation for reduced-rank linear regression equations with noise of arbitrary covariance. The rank-reduced matrix of regression coefficients is parameterized as the product of two full-rank factor matrices. This parameterization is essentially constraint free, but it is not unique, which renders the associated ML estimation problem rath... |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1109/78.553480 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Maximum likelihood estimation,Parameter estimation,Covariance matrix,Linear regression,Equations,White noise,Noise reduction,Performance analysis,Testing,Probability | Likelihood-ratio test,Multivariate statistics,Matrix (mathematics),Estimation theory,Covariance matrix,Statistics,Parameter identification problem,Mathematics,Linear regression,Covariance | Journal |
Volume | Issue | ISSN |
44 | 12 | 1053-587X |
Citations | PageRank | References |
34 | 4.06 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Petre Stoica | 1 | 7959 | 915.30 |
| M. Viberg | 2 | 917 | 188.13 |