AU - Yeganegi, Mohammad Reza AU - Chinipardaz, Rahim TI - State Space Representation of Mixture Autoregressive Model PT - JOURNAL ARTICLE TA - JSS JN - JSS VO - 13 VI - 1 IP - 1 4099 - http://jss.irstat.ir/article-1-345-en.html 4100 - http://jss.irstat.ir/article-1-345-en.pdf SO - JSS 1 AB  - ‎This paper is investigating the mixture autoregressive model with constant mixing weights in state space form and generalization to ARMA mixture model‎. ‎Using a sequential Monte Carlo method‎, ‎the forecasting‎, ‎filtering and smoothing distributions are approximated and parameters f the model is estimated via the EM algorithm‎. ‎The results show the dimension of parameter vector in state space representation reduces‎. ‎The results of the simulation study show that the proposed filtering algorithm has a steady state close to the real values of the state vector‎. ‎Moreover‎, ‎according to simulation results‎, ‎the mean vectors of filtering and smoothing distribution converges to state vector quickly‎. CP - IRAN IN - Department of Statistics‎, ‎Shahid Chamran University of Ahvaz‎, ‎Iran. LG - eng PB - JSS PG - 235 PT - Applied YR - 2019