Statistical Estimation and Classification on Commutative Covariance Structures
Automation and Remote Control
To the optimal identification of multivariate systems under perturbations of unknown covariances
Automation and Remote Control
| Hi-index | 0.00 |
For the multidimensional stochastic systems obeying the regression models with unknown covariances of disturbances, consideration was given to the choice of a covariance model and estimation of its parameters. The invariant behavior of the regression model with the covariance matrix of a special structure was studied. In the problem of identifying the structure of a set of feasible covariance matrices, a procedure of successive testing of hypotheses was proposed. The unbiased and invariant uniformly optimal estimates of the parameters of the observation-based model were determined. The problem of identifying the model of covariances in experiment design with random factors was considered as an example.