Calculation of Joint Return Period for Connected Edge Data
AbstractFor better displaying the statistical properties of measured data, it is particularly important to select a suitable multivariate joint distribution model in ocean engineering. According to the characteristics and properties of Copula functions and the correlation analysis of measured data, the nonlinear relationship between random variables can be captured. Additionally, the models based on the Copula theory have more general applicability. A series of correlation measure index, derived from Copula functions, can expand the correlation measure range among variables. In this paper, by means of the correlation analysis between the annual extreme wave height and the corresponding wind speed, their joint distribution models were studied. The newly established two-dimensional joint distribution functions of the extreme wave height and the corresponding wind speed were compared with the existing two-dimensional joint distributions. View Full-Text
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Liu, G.; Chen, B.; Gao, Z.; Fu, H.; Jiang, S.; Wang, L.; Yi, K. Calculation of Joint Return Period for Connected Edge Data. Water 2019, 11, 300.
Liu G, Chen B, Gao Z, Fu H, Jiang S, Wang L, Yi K. Calculation of Joint Return Period for Connected Edge Data. Water. 2019; 11(2):300.Chicago/Turabian Style
Liu, Guilin; Chen, Baiyu; Gao, Zhikang; Fu, Hanliang; Jiang, Song; Wang, Liping; Yi, Kou. 2019. "Calculation of Joint Return Period for Connected Edge Data." Water 11, no. 2: 300.
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