• Title/Summary/Keyword: empirical copula function

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Residual-based copula parameter estimation (잔차를 이용한 코플라 모수 추정)

  • Na, Okyoung;Kwon, Sunghoon
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.267-277
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    • 2016
  • This paper considers we consider the estimation of copula parameters based on residuals in stochastic regression models. We prove that a semiparametric estimator using residual empirical distributions is consistent under some conditions and apply the results to the copula-ARMA model. We provide simulation results for illustration.

A joint probability distribution model of directional extreme wind speeds based on the t-Copula function

  • Quan, Yong;Wang, Jingcheng;Gu, Ming
    • Wind and Structures
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    • v.25 no.3
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    • pp.261-282
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    • 2017
  • The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

Assessment of the directional extreme wind speeds of typhoons via the Copula function and Monte Carlo simulation

  • Wang, Jingcheng;Quan, Yong;Gu, Ming
    • Wind and Structures
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    • v.30 no.2
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    • pp.141-153
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    • 2020
  • Probabilistic information regarding directional extreme wind speeds is important for the precise estimation of the design wind loads on structures. A joint probability distribution model of directional extreme typhoon wind speeds is established using Monte Carlo simulation and empirical copula function to fully consider the correlations of extreme typhoon wind speeds among the different directions. With this model, a procedure for estimating directional extreme wind speeds for given return periods, which ensures that the overall risk is distributed uniformly by direction, is established. Taking 5 typhoon-prone cities in China as examples, the directional extreme typhoon wind speeds for given return periods estimated by the present method are compared with those estimated by the method proposed by Cook and Miller (1999). Two types of directional factors are obtained based on Cook and Miller (1999) and the UK standard's drafting committee (Standard B, 1997), and the directional risks for the given overall risks are discussed. The influences of the extreme wind speed correlations in the different directions and the simulated typhoon wind speed sample sizes on the estimated extreme wind speeds for a given return period are also discussed.

Modelling and Simulating the Spatio-Temporal Correlations of Clustered Wind Power Using Copula

  • Zhang, Ning;Kang, Chongqing;Xu, Qianyao;Jiang, Changming;Chen, Zhixu;Liu, Jun
    • Journal of Electrical Engineering and Technology
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    • v.8 no.6
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    • pp.1615-1625
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    • 2013
  • Modelling and simulating the wind power intermittent behaviour are the basis of the planning and scheduling studies concerning wind power integration. The wind power outputs are evidently correlated in space and time and bring challenges in characterizing their behaviour. This paper provides a methodology to model and simulate the clustered wind power considering its spatio-temporal correlations using the theory of copula. The sampling approach captures the complex spatio-temporal connections among the wind farms by employing a conditional density function calculated using multidimensional copula function. The empirical study of real wind power measurement shows how the wind power outputs are correlated and how these correlations affect the overall uncertainty of clustered wind power output. The case study validates the simulation technique by comparing the simulated results with the real measurements.

A Study on Measuring the Integrated Risk of Domestic Banks Using the Copula Function (코플라 함수를 이용한 국내 시중은행의 통합위험 측정)

  • Chang, Kyung-Chun;Lee, Sang-Heon;Kim, Hyun-Seok
    • Management & Information Systems Review
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    • v.30 no.4
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    • pp.359-383
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    • 2011
  • One of the representative prudential regulations is the capital regulation. The current regulation and international criteria are just simply adding up the market risk and credit risk. According to the portfolio theory due to diversification effect the total risk is less than the summation of market and credit risk. This paper investigates to verify the existence of diversification effect in measuring the integrated risk of financial firm by the copula function, which is combine the different distribution maintain their propriety. The result of the test shows that in measuring the integrated risk not only the correlation and but also the proprieties of market and credit risk distribution are very important. And the tail of risk distribution is important when measuring the economic capital, especially the external impact to the financial market. This paper's contribution is that the empirical evidence in considering the relationship between market and credit risk the integrated risk is less than sum of them.

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