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Time‐varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

Water resources research, 2016-03, Vol.52 (3), p.2327-2349 [Tạp chí có phản biện]

2016. American Geophysical Union. All Rights Reserved. ;ISSN: 0043-1397 ;EISSN: 1944-7973 ;DOI: 10.1002/2015WR018525

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Nhan đề:
Time‐varying nonstationary multivariate risk analysis using a dynamic Bayesian copula
Tác giả: Sarhadi, Ali ; Burn, Donald H. ; Concepción Ausín, María ; Wiper, Michael P.
Chủ đề: Adaptive sampling ; Anomalies ; Bayesian analysis ; Chains ; Climate ; Climate change ; Climate models ; Climatic extremes ; Computer simulation ; Criteria ; Decision making ; Design ; Design analysis ; Dissolved inorganic carbon ; dynamic Bayesian copula ; Ecological risk assessment ; Estimates ; Extreme values ; Frameworks ; Hydrometeorology ; Markov Chain Monte Carlo sampling ; Markov chains ; Modelling ; Monte Carlo method ; Monte Carlo simulation ; Nonstationary environments ; Parameter estimation ; Parameters ; Probability theory ; Risk analysis ; Risk assessment ; Statistical inference ; Statistical methods ; Time dependence ; time‐varying joint return period ; time‐varying multivariate risk analysis
Là 1 phần của: Water resources research, 2016-03, Vol.52 (3), p.2327-2349
Mô tả: A time‐varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time‐varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time‐varying joint return period for multivariate time‐dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme‐climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long‐term decision making strategies should be updated based on the anomalies of the nonstationary environment. Key Points: A multivariate nonstationary risk framework is proposed by developing a dynamic copula A fully time‐varying joint return period concept is developed for multivariate risk analysis The nature and risk of multidimensional processes are changed over time under climate change
Nơi xuất bản: Washington: Blackwell Publishing Ltd
Ngôn ngữ: English
Số nhận dạng: ISSN: 0043-1397
EISSN: 1944-7973
DOI: 10.1002/2015WR018525
Nguồn: Wiley Blackwell AGU Digital Archive
Alma/SFX Local Collection

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Time‐varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

2016. American Geophysical Union. All Rights Reserved. ;ISSN: 0043-1397 ;EISSN: 1944-7973 ;DOI: 10.1002/2015WR018525

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