Consistent estimator in multivariate errors-in-variables model in the case of unknown error covariance structure

Authors

  • A. G. Kukush
  • M. Ya. Polekha

Abstract

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.

Published

25.08.2007

Issue

Section

Research articles

How to Cite

Kukush, A. G., and M. Ya. Polekha. “Consistent Estimator in Multivariate Errors-in-Variables Model in the Case of Unknown Error Covariance Structure”. Ukrains’kyi Matematychnyi Zhurnal, vol. 59, no. 8, Aug. 2007, pp. 1026–1033, https://umj.imath.kiev.ua/index.php/umj/article/view/3366.