Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis
The main aim of this paper is to perform sensitivity analysis to the specification of prior distributions in a Bayesian analysis setting of STAR models. To achieve this aim, the joint posterior distribution of model order, coefficient, and implicit parameters in the logistic STAR model is first bein...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | English |
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TAYLOR & FRANCIS INC
2017
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/79612 |
| _version_ | 1848764081929977856 |
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| author | Livingston, G. Nur, Darfiana |
| author_facet | Livingston, G. Nur, Darfiana |
| author_sort | Livingston, G. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The main aim of this paper is to perform sensitivity analysis to the specification of prior distributions in a Bayesian analysis setting of STAR models. To achieve this aim, the joint posterior distribution of model order, coefficient, and implicit parameters in the logistic STAR model is first being presented. The conditional posterior distributions are then shown, followed by the design of a posterior simulator using a combination of Metropolis-Hastings, Gibbs Sampler, RJMCMC, and Multiple Try Metropolis algorithms, respectively. Following this, simulation studies and a case study on the prior sensitivity for the implicit parameters are being detailed at the end. |
| first_indexed | 2025-11-14T11:13:41Z |
| format | Journal Article |
| id | curtin-20.500.11937-79612 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:13:41Z |
| publishDate | 2017 |
| publisher | TAYLOR & FRANCIS INC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-796122020-06-15T00:27:24Z Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis Livingston, G. Nur, Darfiana Science & Technology Physical Sciences Statistics & Probability Mathematics Gibbs Sampler algorithm Metropolis-Hastings algorithm Multiple Try Metropolis algorithm Prior sensitivity analysis Reversible Jump MCMC algorithm Smooth Transition Autoregressive (STAR) model 62F15 62M10 65C20 65C40 68U20 TIME-SERIES VARIABLE SELECTION The main aim of this paper is to perform sensitivity analysis to the specification of prior distributions in a Bayesian analysis setting of STAR models. To achieve this aim, the joint posterior distribution of model order, coefficient, and implicit parameters in the logistic STAR model is first being presented. The conditional posterior distributions are then shown, followed by the design of a posterior simulator using a combination of Metropolis-Hastings, Gibbs Sampler, RJMCMC, and Multiple Try Metropolis algorithms, respectively. Following this, simulation studies and a case study on the prior sensitivity for the implicit parameters are being detailed at the end. 2017 Journal Article http://hdl.handle.net/20.500.11937/79612 10.1080/03610918.2016.1161794 English TAYLOR & FRANCIS INC restricted |
| spellingShingle | Science & Technology Physical Sciences Statistics & Probability Mathematics Gibbs Sampler algorithm Metropolis-Hastings algorithm Multiple Try Metropolis algorithm Prior sensitivity analysis Reversible Jump MCMC algorithm Smooth Transition Autoregressive (STAR) model 62F15 62M10 65C20 65C40 68U20 TIME-SERIES VARIABLE SELECTION Livingston, G. Nur, Darfiana Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis |
| title | Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis |
| title_full | Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis |
| title_fullStr | Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis |
| title_full_unstemmed | Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis |
| title_short | Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis |
| title_sort | bayesian inference for smooth transition autoregressive (star) model: a prior sensitivity analysis |
| topic | Science & Technology Physical Sciences Statistics & Probability Mathematics Gibbs Sampler algorithm Metropolis-Hastings algorithm Multiple Try Metropolis algorithm Prior sensitivity analysis Reversible Jump MCMC algorithm Smooth Transition Autoregressive (STAR) model 62F15 62M10 65C20 65C40 68U20 TIME-SERIES VARIABLE SELECTION |
| url | http://hdl.handle.net/20.500.11937/79612 |