On the Estimation of k-Regimes Switching of Mixture Autoregressive Model via Weibull Distributional Random Noise
International Journal of Probability and Statistics
This paper describes regime-switching, full range of shape changing distributions (multimodalities), and cycles traits that were characterized by time-varying series via Weibull distributional noise for time series with fluctuations and long-memory. We developed and established a Weibull Mixture Autoregressive model of k-regimes via WMAR(k; p1, p2, , pk ) with Expectation-Maximization (EM) algorithm adopted as parameter estimation technique. The ergodic process for the WMAR(k; p1, p2, , pk ) model was ascertained via the maximized derivation of the absolute value of the subtraction of its likelihood from its expected likelihood.
Expectation-Maximization, k-regimes, Mixture Autoregressive model, Regime-switching, Weibull Distribution