Title :
A random Least Trimmed Squares identification algorithm
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa city, IA, USA
Abstract :
The least trimmed squares estimator (LTS) is a well known robust estimator in terms of protecting the estimate from the outliers. Its high computational complexity is however a problem in practice. In this paper, we propose a random LTS algorithm which has a low computational complexity that can be calculated a priori as a function of the required error bound and the confidence interval. Moreover, if the number of data points goes to infinite, the algorithm becomes a deterministic one that converges to the true LTS in some probability sense.
Keywords :
computational complexity; estimation theory; identification; least mean squares methods; probability; randomised algorithms; LTS estimator; computational complexity; error bound; least trimmed squares estimator; probability; random least trimmed squares identification algorithm; robust estimator; Cities and towns; Computational complexity; Integrated circuit noise; Least squares approximation; Least squares methods; Probability; Protection; Robustness; System identification; Testing;
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
Print_ISBN :
0-7803-7924-1
DOI :
10.1109/CDC.2003.1271682
