RT Journal Article
T1 Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula
A1 Sarhadi, Ali
A1 Burn, Donald H.
A1 Ausín Olivera, María Concepción
A1 Wiper, Michael Peter
AB 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.
PB American Geophysical Union
PB Wiley
SN 1944-7973
YR 2016
FD 2016-03
LK https://hdl.handle.net/10016/38802
UL https://hdl.handle.net/10016/38802
LA eng
NO We thank the associate editor and three anonymous reviewers whose suggestions helped improve the paper. We acknowledge the CMIP5 climate coupled modelling groups, for producing and making their model outputs available, the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison (PCMDI), which provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The CMIP5 model outputs used in the present study are available from http://cmip-pcmdi.llnl.gov/cmip5/data_portal.html. We also thank the Iran Meteorological Organization (IRIMO) for providing rainfall data recorded at the Tehran synoptic station. Funding support was provided by the Natural Sciences and Engineering Research Council (NSERC) of Canada.
DS e-Archivo
RD 27 jul. 2024