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A Bayesian Approach to Heavy-Tailed Finite Mixture Autoregressive Models

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dc.contributor.author Mahmoudi, Mohammad Reza
dc.contributor.author Maleki, Mohsen
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Nguye, Vu-Thanh
dc.contributor.author Pho, Kim-Hung
dc.date.accessioned 2021-01-07T11:41:59Z
dc.date.available 2021-01-07T11:41:59Z
dc.date.issued 2020-06
dc.identifier.citation Mahmoudi, Mohammad Reza...et al. (2020)."A Bayesian Approach to Heavy-Tailed Finite Mixture Autoregressive Models", Symmetry-Basel, Vol. 12, No. 6. tr_TR
dc.identifier.issn 2073-8994
dc.identifier.uri http://hdl.handle.net/20.500.12416/4448
dc.description.abstract In this paper, a Bayesian analysis of finite mixture autoregressive (MAR) models based on the assumption of scale mixtures of skew-normal (SMSN) innovations (called SMSN-MAR) is considered. This model is not simultaneously sensitive to outliers, as the celebrated SMSN distributions, because the proposed MAR model covers the lightly/heavily-tailed symmetric and asymmetric innovations. This model allows us to have robust inferences on some non-linear time series with skewness and heavy tails. Classical inferences about the mixture models have some problematic issues that can be solved using Bayesian approaches. The stochastic representation of the SMSN family allows us to develop a Bayesian analysis considering the informative prior distributions in the proposed model. Some simulations and real data are also presented to illustrate the usefulness of the proposed models. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.3390/sym12060929 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Gibbs Sampling tr_TR
dc.subject MCMC Method tr_TR
dc.subject Non-Linear Time Series tr_TR
dc.subject Finite Mixture Autoregressive Models tr_TR
dc.subject SMSN Distributions tr_TR
dc.title A Bayesian Approach to Heavy-Tailed Finite Mixture Autoregressive Models tr_TR
dc.type article tr_TR
dc.relation.journal Symmetry-Basel tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 12 tr_TR
dc.identifier.issue 6 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen Edebiyat Fakültesi, Matematik Bölümü tr_TR


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