Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models
Joint Authors
Kaewsompong, Nachatchapong
Maneejuk, Paravee
Yamaka, Woraphon
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-16
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
We propose a high-dimensional copula to model the dependence structure of the seemingly unrelated quantile regression.
As the conventional model faces with the strong assumption of the multivariate normal distribution and the linear dependence structure, thus, we apply the multivariate exchangeable copula function to relax this assumption.
As there are many parameters to be estimated, we consider the Bayesian Markov chain Monte Carlo approach to estimate the parameter interests in the model.
Four simulation studies are conducted to assess the performance of our proposed model and Bayesian estimation.
Satisfactory results from simulation studies are obtained suggesting the good performance and reliability of the Bayesian method used in our proposed model.
The real data analysis is also provided, and the empirical comparison indicates our proposed model outperforms the conventional models in all considered quantile levels.
American Psychological Association (APA)
Kaewsompong, Nachatchapong& Maneejuk, Paravee& Yamaka, Woraphon. 2020. Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models. Complexity،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1143329
Modern Language Association (MLA)
Kaewsompong, Nachatchapong…[et al.]. Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models. Complexity No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1143329
American Medical Association (AMA)
Kaewsompong, Nachatchapong& Maneejuk, Paravee& Yamaka, Woraphon. Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models. Complexity. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1143329
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143329