| نویسندگان | Abbas Khashei Siuki,Ali Shahidi,Mohammad Nazeri Tahroudi |
| نشریه | Meteorological Applications |
| شماره صفحات | 1-12 |
| شماره سریال | 28 |
| شماره مجلد | 5 |
| ضریب تاثیر (IF) | 1.411 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2021 |
| رتبه نشریه | ISI |
| نوع نشریه | چاپی |
| کشور محل چاپ | ایران |
| نمایه نشریه | JCR،Scopus |
چکیده مقاله
copula had a great impact on the study and analysis of dependence structures in various sciences. In multivariate analyses with dimensions of more
than two variables, it is associated with computational complexities that solve
vine copulas and these problems. In this study, in order to provide an approach
to simulate potential evapotranspiration based on meteorological parameters
in Birjand meteorological station from different family copulas including Rvine, independent R-vine, Gaussian, independent Gaussian, C-vine, C-vine
independent, D-vine and D-vine independent were used. In this regard, vine
copula simulation and conditional density were used. In pair correlation analysis of the studied variables using Kendall's tau statistic, dependence structure
confirmed the studied parameters. The results showed a minimum correlation
of 0.32 and a maximum of 0.77. The results of Akaike's information criteria
(AIC), Bayesian information criteria (BIC) and LogLike statistics in evaluating
the performance of vine copula dependency structure introduced the C-vine
copula as the superior copula for analysing the pair dependence of the studied
variables. By introducing the superior dependency structure and internal copulas, the tree sequence of the pair of values under study was obtained. Pair of
simulated values was performed using vine copula. Comparison of Kendall's
tau values in both simulation and observation modes showed that Kendall's
tau values were close to each other in both modes and were approximately
similar. The simulation results of vine copula potential evapotranspiration
values and precipitation, temperature and relative humidity values showed
92% efficiency. The efficiency of C-vine copula in dependence analysis and
simulation of potential evapotranspiration (PET) values is very high, which
shows the ability of vine family copulas in multivariate analysis
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