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
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;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.652373
