Alexandria Engineering JournalThe crucial role of heavy-tailed distributions in the analysis of financial and extreme value phenomena is widely acknowledged; however, there is a scarcity of probability distributions to accurately model such data. In the pursuit of analyzing financial
Yuan Liu, Olayan Albalawi
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A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery [PDF]
Annals of Statistics, 2021 Jianqing Fan, Weichen Wang, Ziwei Zhu
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Robust Sparse Non-Negative Matrix Factorization for Identifying Signals of Interest in Bearing Fault Detection [PDF]
SensorsBearings are among the most failure-prone components in rotating systems, making early fault detection crucial in industrial applications. While recent publications have focused on this issue, challenges remain, particularly in dealing with heavy-tailed ...
Hamid Shiri, Anna Michalak
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Inferring heavy tails of flood distributions through hydrograph recession analysis [PDF]
Hydrology and Earth System Sciences, 2023 Floods are often disastrous due to underestimation of the magnitude of rare events. Underestimation commonly happens when the magnitudes of floods follow a heavy-tailed distribution, but this behavior is not recognized and thus neglected for flood hazard
H.-J. Wang +6 more
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Nonparametric Smoothing for Extremal Quantile Regression with Heavy Tailed Data
Revstat Statistical Journal, 2021 In several different fields, it is interested in analyzing the upper or lower tail quantile of the underlying distribution rather than mean or center quantile.
Takuma Yoshida
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New discrete heavy tailed distributions as models for insurance data.
PLoS ONE, 2023 Although many data sets are discrete and heavy tailed (for example, number of claims and claim amounts if recorded as rounded values), not many discrete heavy tailed distributions are available in the literature.
Saralees Nadarajah, Jiahang Lyu
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A New Class of Heavy-Tailed Distributions: Modeling and Simulating Actuarial Measures
Complexity, 2021 Statistical distributions play a prominent role for modeling data in applied fields, particularly in actuarial, financial sciences, and risk management fields.
Jin Zhao +4 more
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Threshold selection for multivariate heavy-tailed data [PDF]
Extremes, 2018 21 pages, 6 ...
Phyllis Wan, Richard A. Davis
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Searching for Heavy-Tailed Probability Distributions for Modeling Real-World Complex Networks
IEEE Access, 2022 Perhaps the most recent controversial topic in network science research is to determine whether real-world complex networks are scale-free or not. Recently, Broido and Clauset [A.D. Broido, A. Clauset, Nature Communication, 10, 1017 (2019)] asserted that
Tanujit Chakraborty +4 more
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Semiparametric exponential families for heavy-tailed data [PDF]
Biometrika, 2015 To appear in ...
William Fithian, Stefan Wager
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