Results 51 to 60 of about 493 (183)
Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on Copula functions [PDF]
Natural Hazards and Earth System Sciences, 2012 This paper presents an advanced approach to statistically analyse storm surge events. In former studies the highest water level during a storm surge event usually was the only parameter that was used for the statistical assessment.
T. Wahl, C. Mudersbach, J. Jensen
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International Transactions on Electrical Energy Systems, Volume 2026, Issue 1, 2026.In order to accurately evaluate and tap the mutual‐aid capacity potential of interconnected power stations under the scenario of peak‐to‐peak compensation between new energy output and load demand, this paper uses Copula function to describe the correlation structure of wind, light, and load from the perspective of source–load matching, quantify the ...
Chao Ding +6 more
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Journal of Mathematics, Volume 2026, Issue 1, 2026.This paper proposes a novel bivariate odd beta prime Fréchet (BOBPF) distribution constructed through the application of the Farlie–Gumbel–Morgenstern (FGM) copula function. The new model, called the BOBPF‐FGM, is engineered to address the persistent challenge of modeling positively skewed and heavy‐tailed bivariate data that exhibit complex ...
Aliyu Ismail Ishaq +6 more
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Extremal behavior of Archimedean copulas [PDF]
Advances in Applied Probability, 2011 We show how the extremal behavior of d-variate Archimedean copulas can be deduced from their stochastic representation as the survival dependence structure of an ℓ1-symmetric distribution (see McNeil and Nešlehová (2009)). We show that the extremal behavior of the radial part of the representation is determined by its Williamson d-transform. This leads
Larsson, Martin, Nešlehová, Johanna
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Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.The evolution pattern of dam deformation reflects its structural response and operational state. Analyzing this pattern enables effective identification of the probability of deformation anomalies. Deviation reflects the extent to which dam deformation deviates from its expected evolution pattern and serves as an important basis for identifying ...
Xudong Chen +8 more
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Multiplicative Archimedean Copula(乘积阿基米德Copula)
Zhejiang Daxue xuebao. Lixue ban, 2010 在乘法模式下,对阿基米德Copula进行了推广,提出了乘积阿基米德Copula.通过构造两类特殊的乘积阿基米德Copula,举出了若干乘积阿基米德Copula例子,并分析了关于尾部相依性、对称性等方面的性质.最后,在探讨阿基米德Copula和乘积阿基米德Copula的关系中,提出几个值得进一步讨论的问题.
WANGQin(王沁) +2 more
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Local dependence estimation using semiparametric archimedean copulas [PDF]
Canadian Journal of Statistics, 2005 Summary: The authors define a new semiparametric Archimedean copula family which has a flexible dependence structure. The generator of the family is a local interpolation of existing generators. It has locally-defined dependence parameters. The authors present a penalized constrained least-squares method to estimate and smooth these parameters.
Vandenhende, François +1 more
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Copula‐Based Deep Learning Models for Competing Risks
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 18, Issue 6, December 2025.ABSTRACT This study introduces a novel approach to modeling competing risks in survival analysis by integrating learnable Copula functions (Clayton, Frank, and Gaussian) with deep learning architectures, including Convolutional Neural Networks (CNN), Long Short‐Term Memory (LSTM) networks, and a hybrid CNN‐LSTM model.
Jong‐Min Kim, Jihoon Kim, Il Do Ha
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Penerapan Metode GARCH-Vine Copula untuk Estimasi Value at Risk (VaR) pada Portofolio
Jurnal Fourier, 2018 Salah satu alat ukur yang digunakan untuk menghitung risiko portofolio adalah Value at Risk (VaR). Beberapa metode pengukuran VaR mengasumsikan return berdistribusi normal dan ukuran dependensi antar saham menggunakan korelasi linear.
Herida Okta Pintari, Retno Subekti
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Spline approximations to conditional Archimedean copula [PDF]
Stat, 2014 We propose a flexible copula model to describe changes with a covariate in the dependence structure of (conditionally exchangeable) random variables. The starting point is a spline approximation to the generator of an Archimedean copula. Changes in the dependence structure with a covariate x are modelled by flexible regression of the spline ...
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