On the Estimation of k-Regimes Switching of Mixture Autoregressive Model via Weibull Distributional Random Noise
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 A...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
International Journal of Probability and Statistics
2021
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.12493/487 |
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| Summary: | 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. |
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