Fréchet Random Noise for k-Regime-Switching Mixture Autoregressive Model
| dc.contributor.author | Rasaki, Olawale Olanrewaju | |
| dc.contributor.author | Anthony, Gichuhi Waititu | |
| dc.contributor.author | Nafiu, Lukman Abiodun | |
| dc.date.accessioned | 2021-05-13T10:45:18Z | |
| dc.date.available | 2021-05-13T10:45:18Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | This paper describes Fréchet distribution as a random noise for capturing multimodalities, regime-switching and change-points attributed to uniformly time-varying series via causality of fluctuations, extreme values and heavy-tailed time series. Fréchet Mixture Autoregressive (FMAR) model of k-regime-switching, denoted by FMAR(k; p1, p2 ,, pk ) was developed and Expectation-Maximization (EM) algorithm was used as a method of parameter estimation for the embedded coefficients of AR of k-mixing weights and lag pk. The limiting distribution of the FMAR(k; p1, p2 ,, pk ) model via Gnedenko-Fisher Tippet limiting property was derived to asymptotically approach an exponential function. | en_US |
| dc.description.sponsorship | Kabale University | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12493/488 | |
| dc.publisher | American Journal of Mathematics and Statistics | en_US |
| dc.subject | Fréchet distribution, Expectation-Maximization, Gnedenko-Fisher Tippet, k-regime-switching, Mixture Autoregressive, Multimodalities | en_US |
| dc.title | Fréchet Random Noise for k-Regime-Switching Mixture Autoregressive Model | en_US |
| dc.type | Article | en_US |
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