Title :
Maximum likelihood estimation of time-series with Markov regime
Author :
Dey, Shuvashis ; Krishnamurthy, Vikram
Author_Institution :
Dept. of Syst. Eng., Australian Nat. Univ., Canberra, ACT
Abstract :
In this paper, we consider the estimation of various Markov-modulated time-series. We obtain maximum likelihood estimates of the time-series parameters including the Markov chain transition probabilities and the time-series coefficients using the expectation maximization (EM) algorithm. Also the recursive EM algorithm is used to obtain online parameter estimates. Simulation studies show that both algorithms yield satisfactory results
Keywords :
Markov processes; estimation theory; maximum likelihood estimation; optimisation; parameter estimation; probability; time series; Markov chain; Markov regime; expectation maximization; maximum likelihood estimation; parameter estimation; time-series; transition probability; Delay; Integrated circuit modeling; Iterative algorithms; Maximum likelihood estimation; Parameter estimation; Polynomials; Recursive estimation; Switches; Systems engineering and theory; Yttrium;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411365
