Title :
Parameter estimation of time-varying autoregressive models using the Gibbs sampler
Author :
Rajan, J.J. ; Rayner, P.J.W.
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
fDate :
6/22/1995 12:00:00 AM
Abstract :
A method is described for applying a Markov chain Monte Carlo method known as the Gibbs sampler to the problem of estimating the parameters of a flexible time-varying autoregressive (TVAR) model with time dependent coefficients that are stationary stochastic processes
Keywords :
Markov processes; Monte Carlo methods; autoregressive processes; parameter estimation; signal processing; time-varying systems; AR models; Gibbs sampler; Markov chain Monte Carlo method; parameter estimation; stationary stochastic processes; time dependent coefficients; time-varying autoregressive models;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19950761
