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Functional Peaks-over-threshold Analysis [article]

Raphaël de Fondeville, Anthony C. Davison
2022 arXiv   pre-print
We give construction rules, simulation algorithms and inference procedures for generalized r-Pareto processes, discuss model validation, and use the new methodology to study extreme European windstorms  ...  In this paper, we extend peaks-over-threshold analysis to extremes of functional data.  ...  Alexis Berne and Gionata Ghiggi kindly gave us access to the Swiss radar rainfall data, which were originally provided by Meteoswiss.  ... 
arXiv:2002.02711v3 fatcat:upbhieajtrgqlcjggja2tkl4km

Benchmarking Quasi-Steady State Cascading Outage Analysis Methodologies

Pierre Henneaux, Emanuele Ciapessoni, Diego Cirio, Eduardo Cotilla-Sanchez, Ruisheng Diao, Ian Dobson, Anish Gaikwad, Stephen Miller, Milorad Papic, Andrea Pitto, Junjian Qi, Nader Samaan (+3 others)
2018 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)  
The objective of this paper is to benchmark the performance of several widely used QSS cascading outage methodologies.  ...  It implies that there is not yet a standardized way to analyze the risk of cascading outage in power systems, and that the specific tool used by a power system engineer can impact the recommendations.  ...  This is called a "heavy tail" and it implies that large blackouts are rarer than smaller blackouts, but not so rare that their risk is smaller.  ... 
doi:10.1109/pmaps.2018.8440212 fatcat:ckigolxvobcynmckscwqbjehxa

The Total Risk Analysis of Large Dams under Flood Hazards

2018 Water  
probability, so a more reasonable dam flood risk analysis method with fewer application restrictions is needed.  ...  In hydraulic engineering, there is a growing tendency to evaluate dam flood risk based on statistical and probabilistic methods that are unsuitable for the situations with rare historical data or low flood  ...  Conclusions In the study, a new computational methodology of dam risk analysis under flood hazards is proposed and used to assess the total risk rating and risk classes of six large dams in Dadu River  ... 
doi:10.3390/w10020140 fatcat:ic47xqcc75a3ti7wx6omnwxwdu

Approximate Bayesian computing for spatial extremes

Robert J. Erhardt, Richard L. Smith
2012 Computational Statistics & Data Analysis  
The method described utilizes results from spatial statistics and extreme value theory to first model extremes in the weather as a max-stable process, and then use these models to simulate payments for  ...  The second application demonstrates the use of the approximate Bayesian computing method in estimating the risk of crop loss due to an unlikely freeze event in northern Texas. iii M RE = 1 J J j=1  ...  Acknowledgments To Mar and Nolan  ... 
doi:10.1016/j.csda.2011.12.003 fatcat:6kc3ub2cdjfqxcdxyxgur45edu

Probabilistic Quantification in the Analysis of Flood Risks in Cross-Border Areas of Poland and Germany

Łukasz Kuźmiński, Michał Nadolny, Henryk Wojtaszek
2020 Energies  
Exposure to a random hazard, combined with the amount of damage resulting from its potential materialization, is called risk.  ...  The empirical data illustrate the usefulness and universality of probabilistic quantification methods for flood risk analysis.  ...  The presented measures are based on simulating the risk using a model developed with empirical data.  ... 
doi:10.3390/en13226020 fatcat:rducdnfl2rbv3bhcnsqaqwg37m

Quantifying operational risk guided by kernel smoothing and continuous credibility: A practitioner's view

Jim Gustafsson, Jens Perch Nielsen, Paul Pritchard, Dix Roberts
2006 The Journal of Operational Risk  
Non-parametric smoothing techniques are considered along with a parametric base with a particular view to comparison with extreme value theory.  ...  The evolutionary nature of operational risk modeling to establish capital charges is recognized, emphasizing the importance of capturing tail behavior.  ...  A commonly applied technique in operational risk is extremevalue theory which offers a broadly accepted methodology for estimating the tail of a distribution (and hence dealing with large, rare loss events  ... 
doi:10.21314/jop.2006.005 fatcat:dzm4lfulu5d2tf7dxmga6zaxiq

Quantifying Operational Risk Guided by Kernel Smoothing and Continuous Credibility: A Practitioners View

Jim Gustafsson, Jens Perch Nielsen, Paul Pritchard, Dix Roberts
2006 Social Science Research Network  
Non-parametric smoothing techniques are considered along with a parametric base with a particular view to comparison with extreme value theory.  ...  The evolutionary nature of operational risk modeling to establish capital charges is recognized, emphasizing the importance of capturing tail behavior.  ...  A commonly applied technique in operational risk is extremevalue theory which offers a broadly accepted methodology for estimating the tail of a distribution (and hence dealing with large, rare loss events  ... 
doi:10.2139/ssrn.880361 fatcat:s3elm2me4fdrrcmgimm2ktfmiq

Quantifying Operational Risk Guided by Kernel Smoothing and Continuous Credibility

Jim Gustafsson, Jens Perch Nielsen, Paul Pritchard, Dix Roberts
2005 Social Science Research Network  
Non-parametric smoothing techniques are considered along with a parametric base with a particular view to comparison with extreme value theory.  ...  The evolutionary nature of operational risk modeling to establish capital charges is recognized, emphasizing the importance of capturing tail behavior.  ...  A commonly applied technique in operational risk is extremevalue theory which offers a broadly accepted methodology for estimating the tail of a distribution (and hence dealing with large, rare loss events  ... 
doi:10.2139/ssrn.627342 fatcat:rg5fjkoypvdflakylluasmbb6i

Robust prediction of failure time through unified Bayesian analysis of nonparametric transformation models [article]

Chong Zhong, Junshan Shen, Jin Yang, Catherine Liu
2022 arXiv   pre-print
To facilitate applicability of these new priors, we subtly impose an exponential transformation on top of NTMs, which compresses the space of infinite-dimensional parameters to positive quadrants while  ...  Utilizing a Bayesian workflow, we address the challenge by constructing new weakly informative nonparametric priors for infinite-dimensional parameters so as to remedy flat likelihoods associated with  ...  survival probability, cumulative hazards, and relative risk scores, not restricting applications to aforementioned three mainstay transformation models.  ... 
arXiv:2205.14504v2 fatcat:dueyzgpsjnhxndnsize3smuzp4

Bayesian binary quantile regression for the analysis of Bachelor-to-Master transition

Cristina Mollica, Lea Petrella
2016 Journal of Applied Statistics  
methods for Predictive and Exploratory Path modeling  ...  Specialized teams Currently the ERCIM WG has over 1150 members and the following specialized teams BM: Bayesian Methodology CODA: Complex data structures and Object Data Analysis CPEP: Component-based  ...  The new methodology is illustrated by simulations and real data applications.  ... 
doi:10.1080/02664763.2016.1263835 fatcat:l5eyielgxrct7hq5ljqeej5ccy

Have applications of continuous rainfall-runoff simulation realized the vision for process-based flood frequency analysis?

Rob Lamb, Duncan Faulkner, Paul Wass, David Cameron
2016 Hydrological Processes  
for flood risk decision-making than would have been possible using standard methods.  ...  It reviews the generic methodology and illustrates applications of the original vision for a more physically-realistic approach to flood frequency analysis through a set of practical case studies, highlighting  ...  We are grateful to these organisations for permission to reproduce data from the above studies. We thank John England (USACE) and the anonymous reviewer for their constructive review comments.  ... 
doi:10.1002/hyp.10882 fatcat:txooyb46pfffhb66oml3y2bhg4

A sequential distance-based approach for imputing missing data: Forward Imputation

Nadia Solaro, Alessandro Barbiero, Giancarlo Manzi, Pier Alda Ferrari
2016 Advances in Data Analysis and Classification  
The first is given by Andrew Harvey (Dynamic models for volatility and heavy tails) at 09:00-14:00. The second tutorial is given by Hans-Georg Müller (Functional data analysis) at 15:15-20:00.  ...  At the same time, rare extreme events and the tail behavior of financial time series are of increasing interest, especially in the context of risk measurement and risk management.  ... 
doi:10.1007/s11634-016-0243-0 fatcat:yvrqlgllsbesbnvnzzci2egpl4

Nonstationary Extreme Value Analysis of Nearshore Sea-State Parameters under the Effects of Climate Change: Application to the Greek Coastal Zone and Port Structures

Panagiota Galiatsatou, Christos Makris, Yannis Krestenitis, Panagiotis Prinos
2021 Journal of Marine Science and Engineering  
The proposed methodology hinges on the extraction of extreme wave characteristics and sea levels due to storm events affecting the coast, a nonstationary extreme value analysis of sea-state parameters  ...  In the present work, a methodological framework, based on nonstationary extreme value analysis of nearshore sea-state parameters, is proposed for the identification of climate change impacts on coastal  ...  This response function provided the sample of multivariate maxima used in hazard analysis.  ... 
doi:10.3390/jmse9080817 fatcat:zmxkadwc5zfxzjkbux7z2gifee

ARAMIS heritage, 10 years after the end of the project [chapter]

2017 Risk Analysis and Management - Trends, Challenges and Emerging Issues  
Although all care is taken to ensure integrity and the quality of this publication and the information herein, no responsibility is assumed by the publishers nor the author for any damage to the property  ...  or persons as a result of operation or use of this publication and/or the information contained herein.  ...  MATRIX (New methodologies for multi-hazard and multi-risk assessment methods for Europe), EU funded FP7 project. Merz, B., Thieken, A.H. (2005) .  ... 
doi:10.1201/9781315265339-9 fatcat:rs6apsg5rndttgq7fi5huiukry

Benchmarking and Validation of Cascading Failure Analysis Tools

Janusz Bialek, Emanuele Ciapessoni, Diego Cirio, Eduardo Cotilla-Sanchez, Chris Dent, Ian Dobson, Pierre Henneaux, Paul Hines, Jorge Jardim, Stephen Miller, Mathaios Panteli, Milorad Papic (+3 others)
2016 IEEE Transactions on Power Systems  
Additional information: Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational  ...  Further information on publisher's website: http://dx.any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works  ...  An important feature of these distributions is the heavy tail, which indicates that larger blackouts are more likely than predicted by conventional risk analysis methods.  ... 
doi:10.1109/tpwrs.2016.2518660 fatcat:ef2zybmhtrexvi3txkwuz4keoy
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