Consistent estimator in multivariate errors-in-variables model in the case of unknown error covariance structure
We consider a linear multivariate errors-in-variables model AX ? B, where the matrices A and B are observed with errors and the matrix parameter X is to be estimated. In the case of lack of information about the error covariance structure, we propose an estimator that converges in probability to X as the number of rows in A tends to infinity. Sufficient conditions for this convergence and for the asymptotic normality of the estimator are found.
English version (Springer): Ukrainian Mathematical Journal 59 (2007), no. 8, pp 1137-1147.
Citation Example: Kukush A. G., Polekha M. Ya. Consistent estimator in multivariate errors-in-variables model in the case of unknown error covariance structure // Ukr. Mat. Zh. - 2007. - 59, № 8. - pp. 1026–1033.