Title :
Truncated ML estimation of transition probabilities for systems with interrupted observations
Author_Institution :
The University of Iowa, Iowa City, Iowa
Abstract :
A linear discrete-time system with interrupted observations is considered. The interrupted observation mechanism is expressed in terms of a two-state Markov chain. The transition probability matrix of the Markov chain is unknown and is assumed to belong to a compact set. A novel scheme, called truncated maximum likelihood estimation, is proposed for consistent estimation of the transition probabilities. Conditions for weak consistency are investigated.
Keywords :
Bayesian methods; Cities and towns; Convergence; Equations; Linear systems; Maximum likelihood estimation; State estimation;
Conference_Titel :
Decision and Control including the Symposium on Adaptive Processes, 1980 19th IEEE Conference on
Conference_Location :
Albuquerque, NM, USA
DOI :
10.1109/CDC.1980.271860
