Title :
Bias and mean square error properties of general estimators
Author_Institution :
Systems Control, Inc., Palo Alto, CA
Abstract :
This paper uses high order sensitivity analysis for the determination of bias and mean square errors of general estimators with finite and infinite samples. The errors in maximum likelihood estimates are analyzed in detail. It is Shown that in finite data, the maximum likelihood estimates may be substantially biased and possess mean square errors substantially higher than Cramer-Rao bounds. The errors caused by inaccurate models are determined, leading to a technique for selection of parameters in practical estimation problems.
Keywords :
Control systems; Error correction; Estimation error; Maximum likelihood estimation; Mean square error methods; Parameter estimation; Robustness;
Conference_Titel :
Decision and Control including the 15th Symposium on Adaptive Processes, 1976 IEEE Conference on
Conference_Location :
Clearwater, FL, USA
DOI :
10.1109/CDC.1976.267804
