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Статті в журналах з теми "Extremal dependence modeling"
Barro, Diakarya. "Extremal Dependence Modeling with Spatial and Survival Distributions." Journal of Mathematics Research 9, no. 1 (January 23, 2017): 127. http://dx.doi.org/10.5539/jmr.v9n1p127.
Повний текст джерелаHuser, Raphaël, and Jennifer L. Wadsworth. "Modeling Spatial Processes with Unknown Extremal Dependence Class." Journal of the American Statistical Association 114, no. 525 (June 28, 2018): 434–44. http://dx.doi.org/10.1080/01621459.2017.1411813.
Повний текст джерелаMallam, Hassane Abba, Natatou Dodo Moutari, Barro Diakarya, and Saley Bisso. "Extremal Copulas and Tail Dependence in Modeling Stochastic Financial Risk." European Journal of Pure and Applied Mathematics 14, no. 3 (August 5, 2021): 1057–81. http://dx.doi.org/10.29020/nybg.ejpam.v14i3.3951.
Повний текст джерелаApputhurai, P., and A. G. Stephenson. "Accounting for uncertainty in extremal dependence modeling using Bayesian model averaging techniques." Journal of Statistical Planning and Inference 141, no. 5 (May 2011): 1800–1807. http://dx.doi.org/10.1016/j.jspi.2010.11.038.
Повний текст джерелаRessel, Paul. "Stable tail dependence functions – some basic properties." Dependence Modeling 10, no. 1 (January 1, 2022): 225–35. http://dx.doi.org/10.1515/demo-2022-0114.
Повний текст джерелаChen, Zaoli, and Gennady Samorodnitsky. "Extremal clustering under moderate long range dependence and moderately heavy tails." Stochastic Processes and their Applications 145 (March 2022): 86–116. http://dx.doi.org/10.1016/j.spa.2021.12.001.
Повний текст джерелаOlinda, R. A., J. Blanchet, C. A. C. dos Santos, V. A. Ozaki, and P. J. Ribeiro Jr. "Spatial extremes modeling applied to extreme precipitation data in the state of Paraná." Hydrology and Earth System Sciences Discussions 11, no. 11 (November 17, 2014): 12731–64. http://dx.doi.org/10.5194/hessd-11-12731-2014.
Повний текст джерелаLi, Jiayi, Zhiyan Cai, Yixuan Liu, and Chengxiu Ling. "Extremal Analysis of Flooding Risk and Its Catastrophe Bond Pricing." Mathematics 11, no. 1 (December 27, 2022): 114. http://dx.doi.org/10.3390/math11010114.
Повний текст джерелаSaunina, A. Yu, V. R. Nikitenko, A. A. Chistyakov, M. A. Zvaizgne, A. R. Tameev, and A. E. Aleksandrov. "Analytic Modeling of the of J–V Characteristics of Quantum Dot-Based Photovoltaic Cells." International Journal of Nanoscience 18, no. 03n04 (April 2, 2019): 1940083. http://dx.doi.org/10.1142/s0219581x19400830.
Повний текст джерелаFerreira, Helena, and Marta Ferreira. "The stopped clock model." Dependence Modeling 10, no. 1 (January 1, 2022): 48–57. http://dx.doi.org/10.1515/demo-2022-0101.
Повний текст джерелаДисертації з теми "Extremal dependence modeling"
Kereszturi, Monika. "Assessing and modelling extremal dependence in spatial extremes." Thesis, Lancaster University, 2017. http://eprints.lancs.ac.uk/86369/.
Повний текст джерелаLecei, Ivan [Verfasser]. "Modelling extremal dependence / Ivan Lecei." Ulm : Universität Ulm, 2018. http://d-nb.info/1173249745/34.
Повний текст джерелаJohnson, Jill Suzanne. ""Modelling Dependence in Extreme Environmental Events"." Thesis, University of Newcastle upon Tyne, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525050.
Повний текст джерелаNavarrete, Miguel A. Ancona. "Dependence modelling and spatial prediction for extreme values." Thesis, Lancaster University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369658.
Повний текст джерелаEriksson, Kristofer. "Risk Measures and Dependence Modeling in Financial Risk Management." Thesis, Umeå universitet, Institutionen för fysik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-85185.
Повний текст джерелаSingh, Abhay Kumar. "Modelling Extreme Market Risk - A Study of Tail Related Risk Measures." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2011. https://ro.ecu.edu.au/theses/417.
Повний текст джерелаBoulin, Alexis. "Partitionnement des variables de séries temporelles multivariées selon la dépendance de leurs extrêmes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ5039.
Повний текст джерелаIn a wide range of applications, from climate science to finance, extreme events with a non-negligible probability can occur, leading to disastrous consequences. Extremes in climatic events such as wind, temperature, and precipitation can profoundly impact humans and ecosystems, resulting in events like floods, landslides, or heatwaves. When the focus is on studying variables measured over time at numerous specific locations, such as the previously mentioned variables, partitioning these variables becomes essential to summarize and visualize spatial trends, which is crucial in the study of extreme events. This thesis explores several models and methods for partitioning the variables of a multivariate stationary process, focusing on extreme dependencies.Chapter 1 introduces the concepts of modeling dependence through copulas, which are fundamental for extreme dependence. The notion of regular variation, essential for studying extremes, is introduced, and weakly dependent processes are discussed. Partitioning is examined through the paradigms of separation-proximity and model-based clustering. Non-asymptotic analysis is also addressed to evaluate our methods in fixed dimensions.Chapter 2 study the dependence between maximum values is crucial for risk analysis. Using the extreme value copula function and the madogram, this chapter focuses on non-parametric estimation with missing data. A functional central limit theorem is established, demonstrating the convergence of the madogram to a tight Gaussian process. Formulas for asymptotic variance are presented, illustrated by a numerical study.Chapter 3 proposes asymptotically independent block (AI-block) models for partitioning variables, defining clusters based on the independence of maxima. An algorithm is introduced to recover clusters without specifying their number in advance. Theoretical efficiency of the algorithm is demonstrated, and a data-driven parameter selection method is proposed. The method is applied to neuroscience and environmental data, showcasing its potential.Chapter 4 adapts partitioning techniques to analyze composite extreme events in European climate data. Sub-regions with dependencies in extreme precipitation and wind speed are identified using ERA5 data from 1979 to 2022. The obtained clusters are spatially concentrated, offering a deep understanding of the regional distribution of extremes. The proposed methods efficiently reduce data size while extracting critical information on extreme events.Chapter 5 proposes a new estimation method for matrices in a latent factor linear model, where each component of a random vector is expressed by a linear equation with factors and noise. Unlike classical approaches based on joint normality, we assume factors are distributed according to standard Fréchet distributions, allowing a better description of extreme dependence. An estimation method is proposed, ensuring a unique solution under certain conditions. An adaptive upper bound for the estimator is provided, adaptable to dimension and the number of factors
Ayari, Samia. "Nonparametric estimation of the dependence function for multivariate extreme value distributions." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4078.
Повний текст джерелаIn this thesis, we investigate the nonparametric estimation of the dependence function for multivariate extreme value distributions. Firstly, we assume independent and identically distributed random variables (i.i.d). Several nonparametric estimators are compared for a trivariate dependence function of logistic type in two different cases. In a first analysis, we suppose that marginal functions are generalized extreme value distributions. In a second investigation, we substitute the marginal function by the empirical distribution function. Monte Carlo simulations show that the Gudendorf-Segers (Gudendorf and Segers, 2011) estimator outperforms the other estimators for different sample sizes. Secondly, we drop the i.i.d assumption as it’s not verified in time series analysis. Considering the univariate framework, we examine the extremal behavior of a stationary Gaussian autoregressive process. In the multivariate setting, we prove the asymptotic consistency of the Pickands dependence function estimator. This theoretical finding is confirmed by empirical investigations in the asymptotic independence case as well as the asymptotic dependence case. Finally, the Gudendorf-Segers estimator is used to model the dependence structure of extreme ozone concentrations in locations that record several exceedances for both guideline and limit values of the Tunisian air quality standard NT.106.04
Kyselá, Eva. "Modelling portfolios with heavy-tailed risk factors." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-264017.
Повний текст джерелаSchulz, Thorsten [Verfasser], Matthias [Akademischer Betreuer] [Gutachter] Scherer, Griselda [Gutachter] Deelstra, and Ralf [Gutachter] Werner. "Stochastic dependencies in derivative pricing: Decoupled BNS-volatility, sequential modeling of jumps, and extremal WWR / Thorsten Schulz ; Gutachter: Matthias Scherer, Griselda Deelstra, Ralf Werner ; Betreuer: Matthias Scherer." München : Universitätsbibliothek der TU München, 2017. http://d-nb.info/1147566003/34.
Повний текст джерелаКниги з теми "Extremal dependence modeling"
Gao, Yanhong, and Deliang Chen. Modeling of Regional Climate over the Tibetan Plateau. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.591.
Повний текст джерелаЧастини книг з теми "Extremal dependence modeling"
Ortego, María I., Juan J. Egozcue, and Raimon Tolosana-Delgado. "Modeling Extremal Dependence Using Copulas. Application to Rainfall Data." In Lecture Notes in Earth System Sciences, 53–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32408-6_13.
Повний текст джерелаPraprom, Chakorn, and Songsak Sriboonchitta. "Extreme Value Copula Analysis of Dependences between Exchange Rates and Exports of Thailand." In Modeling Dependence in Econometrics, 187–99. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03395-2_12.
Повний текст джерелаBoonyanuphong, Phattanan, and Songsak Sriboonchitta. "An Analysis of Volatility and Dependence between Rubber Spot and Futures Prices Using Copula-Extreme Value Theory." In Modeling Dependence in Econometrics, 431–44. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03395-2_27.
Повний текст джерелаKaewkheaw, Mutita, Pisit Leeahtam, and Chukiat Chaiboosri. "An Analysis of Relationship between Gold Price and U.S. Dollar Index by Using Bivariate Extreme Value Copulas." In Modeling Dependence in Econometrics, 455–62. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03395-2_29.
Повний текст джерелаColes, Stuart. "Extremes of Dependent Sequences." In An Introduction to Statistical Modeling of Extreme Values, 92–104. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-3675-0_5.
Повний текст джерелаTaylor, John, and Jay Larson. "Resolution Dependence in Modeling Extreme Weather Events." In Computational Science — ICCS 2001, 204–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45545-0_29.
Повний текст джерелаWeissman, Ishay. "On Some Dependence Measures for Multivariate Extreme Value Distributions." In Advances in Mathematical and Statistical Modeling, 171–80. Boston: Birkhäuser Boston, 2008. http://dx.doi.org/10.1007/978-0-8176-4626-4_12.
Повний текст джерела"Nonparametric Estimation of Extremal Dependence Anna Kiriliouk, Johan Segers, and Michał Warchoł." In Extreme Value Modeling and Risk Analysis, 373–96. Chapman and Hall/CRC, 2016. http://dx.doi.org/10.1201/b19721-21.
Повний текст джерелаSmith, Elizabeth L., and David Walshaw. "Modelling Bivariate Extremes in a Region." In Bayesian Statistics 7, 681–90. Oxford University PressOxford, 2003. http://dx.doi.org/10.1093/oso/9780198526155.003.0048.
Повний текст джерела"Extreme Dependence Models." In Extreme Value Modeling and Risk Analysis, 345–72. Chapman and Hall/CRC, 2016. http://dx.doi.org/10.1201/b19721-20.
Повний текст джерелаТези доповідей конференцій з теми "Extremal dependence modeling"
Towe, Ross, Emma Eastoe, Jonathan Tawn, Yanyun Wu, and Philip Jonathan. "The Extremal Dependence of Storm Severity, Wind Speed and Surface Level Pressure in the Northern North Sea." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10154.
Повний текст джерела"Evaluating extremal dependence in stock markets using Extreme Value Theory." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.d6.singh2.
Повний текст джерелаMcDonald, Andrew, Pang-Ning Tan, and Lifeng Luo. "COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/462.
Повний текст джерелаWada, Ryota, Philip Jonathan, Takuji Waseda, and Shejun Fan. "Estimating Extreme Waves in the Gulf of Mexico Using a Simple Spatial Extremes Model." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95442.
Повний текст джерелаVanem, Erik, Øystein Lande, and Elias Fekhari. "A Simulation Study on the Usefulness of the Bernstein Copula for Statistical Modeling of Metocean Variables." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-121159.
Повний текст джерелаBarbariol, Francesco, Alvise Benetazzo, Filippo Bergamasco, Sandro Carniel, and Mauro Sclavo. "Stochastic Space-Time Extremes of Wind Sea States: Validation and Modeling." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-23997.
Повний текст джерелаWada, Ryota, Philip Jonathan, and Takuji Waseda. "Spatial Features of Extreme Waves in Gulf of Mexico." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-19190.
Повний текст джерелаYu, Hang, Zheng Choo, Justin Dauwels, Philip Jonathan, and Qiao Zhou. "Modeling spatially-dependent extreme events with Markov random field priors." In 2012 IEEE International Symposium on Information Theory - ISIT. IEEE, 2012. http://dx.doi.org/10.1109/isit.2012.6283503.
Повний текст джерелаVanem, Erik. "Stochastic Models for Long-Term Prediction of Extreme Waves: A Literature Survey." In ASME 2010 29th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/omae2010-20076.
Повний текст джерелаMackay, E. B. L., C. J. R. Murphy-Barltrop, and P. Jonathan. "The SPAR Model: A New Paradigm for Multivariate Extremes. Application to Joint Distributions of Metocean Variables." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-130932.
Повний текст джерелаЗвіти організацій з теми "Extremal dependence modeling"
Furman, Alex, Jan Hopmans, Shmuel Assouline, Jirka Simunek, and Jim Richards. Soil Environmental Effects on Root Growth and Uptake Dynamics for Irrigated Systems. United States Department of Agriculture, February 2011. http://dx.doi.org/10.32747/2011.7592118.bard.
Повний текст джерелаOliynyk, Kateryna, and Matteo Ciantia. Application of a finite deformation multiplicative plasticity model with non-local hardening to the simulation of CPTu tests in a structured soil. University of Dundee, December 2021. http://dx.doi.org/10.20933/100001230.
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