Modified inference function for margins for the bivariate clayton copula-based SUN Tobit Model

Louzada, Francisco; Ferreira, Paulo H.

doi:10.1080/02664763.2016.1155204

Cited by 13 publications

(9 citation statements)

References 36 publications

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“…Pastpipatkul et al [9] used the copula to join the errors of the SUR model. Louzada and Ferreira [10] also suggested using the Clayton copula to join the error terms of the bivariate seemingly unrelated regression (SUN) tobit model. ey mentioned that their model has the ability to capture the lower tail dependence of the SUN model.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

2020

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We propose a high-dimensional copula to model the dependence structure of the seemingly unrelated quantile regression. As the conventional model faces with the strong assumption of the multivariate normal distribution and the linear dependence structure, thus, we apply the multivariate exchangeable copula function to relax this assumption. As there are many parameters to be estimated, we consider the Bayesian Markov chain Monte Carlo approach to estimate the parameter interests in the model. Four simulation studies are conducted to assess the performance of our proposed model and Bayesian estimation. Satisfactory results from simulation studies are obtained suggesting the good performance and reliability of the Bayesian method used in our proposed model. The real data analysis is also provided, and the empirical comparison indicates our proposed model outperforms the conventional models in all considered quantile levels.

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Section: Introductionmentioning

confidence: 99%

“…Absolute Bias (first column) and MSE (second column) of the estimates of θ α Gu , θ α C , θ α F at different quantile levels, α � (0.25, 0.50, 0.75), where R � 1,000 repetitions 10. Complexity volatile and might exhibit nonnormal distribution.…”

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confidence: 99%

Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

2020

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“…In our future study, we would extend our copula method to a multivariate case, to develop a generalized composite operator of asymmetric copula family as in Louzada and Ferreira (2016), to apply to the direction data from Kim and Kim (2014), and to incorporate time varying component as in Ara et al (2017) to our proposed method. R program and datasets are available upon request from the corresponding author.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Construction of bivariate asymmetric copulas

Mukherjee

Lee

Kim

et al. 2018

CSAM

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Copulas are a tool for constructing multivariate distributions and formalizing the dependence structure between random variables. From copula literature review, there are a few asymmetric copulas available so far while data collected from the real world often exhibit asymmetric nature. This necessitates developing asymmetric copulas. In this study, we discuss a method to construct a new class of bivariate asymmetric copulas based on products of symmetric (sometimes asymmetric) copulas with powered arguments in order to determine if the proposed construction can offer an added value for modeling asymmetric bivariate data. With these newly constructed copulas, we investigate dependence properties and measure of association between random variables. In addition, the test of symmetry of data and the estimation of hyper-parameters by the maximum likelihood method are discussed. With two real example such as car rental data and economic indicators data, we perform the goodness-of-fit test of our proposed asymmetric copulas. For these data, some of the proposed models turned out to be successful whereas the existing copulas were mostly unsuccessful. The method of presented here can be useful in fields such as finance, climate and social science.

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“…Supposing that φθ(t)=t−θ−1 and θ>0, φθ(t) is completely monotonous on [0,∞). For n≥2, the Clayton Copula function can be expressed as:Cθn(u)=(u1−θ+u2−θ+⋯+un−θ−n+1)true−1θwhere θ denotes the Copula parameters, which can be solved by the Inference Functions for Margins (IFM) [24,25]. Compared with the maximum likelihood estimation, the IFM has more advantages for numerical calculations and the progressive effect.…”

Section: Methods Of Modeling the Reliability While Considering The mentioning

confidence: 99%

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

et al. 2019

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Lithium-ion batteries are widely used as basic power supplies and storage units for large-scale electric drive products such as electric vehicles. Their reliability is directly related to the life and safe operation of the electric drive products. In fact, the cells have a dependent relationship with the degradation process and they affect the degradation rate of the entire battery pack, thereby affecting its reliability. At present, most research focuses on the reliability of battery packs and assumes that their cells are independent of each other, which may cause the reliability of the evaluation to deviate greatly from the actual level. In order to accurately assess the reliability of lithium-ion batteries, it is necessary to build a reliability model considering the dependency among cells for the overall degradation of lithium-ion battery packs. Therefore, in this study, based on a lithium-ion battery degradation test, the Wiener process is used to analyze the reliability of four basic configurations of lithium-ion battery packs. According to the degradation data of the battery packs, the Copula function is used to quantitatively describe the dependent relationship in the degradation process of a single battery, and the quantitative dependent relationship is combined with the reliability model to form a new reliability model. Finally, taking the battery system of Tesla S as an example, a feasible optimization method for battery pack design is provided based on the model constructed in this work.

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Modified inference function for margins for the bivariate clayton copula-based SUN Tobit Model

Cited by 13 publications

References 36 publications

Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

Construction of bivariate asymmetric copulas

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

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