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On bad data suppression in estimation

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1 Author(s)
Kohlas, J. ; Brown Boveri Research Center, Baden, Switzerland

Merrill and Schweppe [1] propose a modification of the usual least squares criterion for estimation in order to suppress bad data. It is shown that similar estimators can be obtained from maximum likelihood theory.

Published in:

Automatic Control, IEEE Transactions on  (Volume:17 ,  Issue: 6 )