Name
Title | ||
|---|---|---|
Maximum likelihood recursive least squares estimation for multivariate equation-error ARMA systems. |
Abstract | ||
|---|---|---|
This paper focuses on the parameter estimation problems of multivariate equation-error systems. A recursive generalized extended least squares algorithm is presented as a comparison. Based on the maximum likelihood principle and the coupling identification concept, the multivariate equation-error system is decomposed into several regressive identification models, each of which has only a parameter vector, and a coupled subsystem maximum likelihood recursive least squares identification algorithm is developed for estimating the parameter vectors of these submodels. The simulation example shows that the proposed algorithm is effective and has high estimation accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jfranklin.2018.07.041 | Journal of the Franklin Institute |
Field | DocType | Volume |
Applied mathematics,Mathematical optimization,Coupling,Maximum likelihood principle,Multivariate statistics,Maximum likelihood,Estimation theory,Recursive least squares filter,Recursion,Extended least squares,Mathematics | Journal | 355 |
Issue | ISSN | Citations |
15 | 0016-0032 | 0 |
PageRank | References | Authors |
0.34 | 25 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lijuan Liu | 1 | 0 | 1.01 |
| Yan Wang | 2 | 54 | 12.95 |
| Cheng Wang | 3 | 0 | 1.01 |
| Feng Ding | 4 | 4973 | 231.42 |
| Tasawar Hayat | 5 | 999 | 71.98 |