On the Estimation of k-Regimes Switching of Mixture Autoregressive Model via Weibull Distributional Random Noise
| dc.contributor.author | Rasaki, Olawale Olanrewaju | |
| dc.contributor.author | Anthony, Gichuhi Waititu | |
| dc.contributor.author | Nafiu, Lukman Abiodun | |
| dc.date.accessioned | 2021-05-13T10:38:11Z | |
| dc.date.available | 2021-05-13T10:38:11Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | 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. | en_US |
| dc.description.sponsorship | Kabale University | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12493/487 | |
| dc.publisher | International Journal of Probability and Statistics | en_US |
| dc.subject | Expectation-Maximization, k-regimes, Mixture Autoregressive model, Regime-switching, Weibull Distribution | en_US |
| dc.title | On the Estimation of k-Regimes Switching of Mixture Autoregressive Model via Weibull Distributional Random Noise | en_US |
| dc.type | Article | en_US |
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