Consistent estimation in the bilinear multivariate errors-in-variables model

Abstract

Abstract. A bilinear multivariate errors-in-variables model is considered. It corresponds to an overdetermined set of linear equations AXB ¼ C, A A R mÂn , B A R pÂq , in which the data A, B, C are perturbed by errors. The total least squares estimator is inconsistent in this case.An adjusted least squares estimatorX X is constructed, which converges to the true value X, as m ! y, q ! y. A small sample modification of the estimator is presented, which is more stable for small m and q and is asymptotically equivalent to the adjusted least squares estimator. The theoretical results are confirmed by a simulation study.

Frisch scheme identification for dynamic diagonal bilinear models

“…Some approaches that address the general polynomial non-linear EIV problem, e.g. Vajk and Hetthe´ssy (2003), or the bilinear EIV problem, see Kukush, Markovsky, and Van Huffel (2003), have been proposed. However, these methods are limited to the static EIV case exclusively.…”