DocumentCode
319976
Title
Consistency of the MLE for jump Markov autoregressive systems
Author
Krishnamurthy, Vikram ; Ryden, Tobias
Author_Institution
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume
4
fYear
1997
fDate
10-12 Dec 1997
Firstpage
3401
Abstract
An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time-point is given by a (non-observable) Markov chain. We examine maximum-likelihood estimation for such models and show consistency of a conditional MLE. Also identifiability issues are discussed
Keywords
Markov processes; autoregressive processes; maximum likelihood estimation; identifiability; jump Markov autoregressive systems; maximum-likelihood estimation; nonobservable Markov chain; regression function; Autoregressive processes; Communication networks; Hidden Markov models; Mathematical model; Maximum likelihood estimation; Physiology; Random variables; Recursive estimation; Speech recognition; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location
San Diego, CA
ISSN
0191-2216
Print_ISBN
0-7803-4187-2
Type
conf
DOI
10.1109/CDC.1997.652373
Filename
652373
Link To Document