Results 31 to 40 of about 14,911 (257)
Understanding Heavy Tails of Flood Peak Distributions [PDF]
AbstractStatistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail ...
Bruno Merz +11 more
openaire +4 more sources
The Random Effect Transformation for Three Regularity Classes
We continue the analysis of the influence of the random effect transformation on the regularity of distribution functions. The paper considers three regularity classes: heavy-tailed distributions, distributions with consistently varying tails, and ...
Jonas Šiaulys +2 more
doaj +1 more source
Heavy-Tailed Distributions in VaR Calculations [PDF]
Market risks are the prospect of financial losses – or gains – due to unexpected changes in market prices and rates. Evaluating the exposure to such risks is nowadays of primary concern to risk managers in financial and non-financial institutions alike. Since the early 1990s a commonly used market risk estimation methodology has been the Value at Risk (
Adam Misiorek, Rafal Weron
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Heavy-Tailed Distributions and Rating [PDF]
AbstractIn this paper we consider the problem raised in the Astin Bulletin (1999) by Prof. Benktander at the occasion of his 80th birthday concerning the choice of an appropriate claim size distribution in connection with reinsurance rating problems. Appropriate models for large claim distributions play a central role in this matter.
J. Beirlant, G. Matthys, G. Dierckx
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Type-I heavy tailed family with applications in medicine, engineering and insurance.
In the present study, a new class of heavy tailed distributions using the T-X family approach is introduced. The proposed family is called type-I heavy tailed family. A special model of the proposed class, named Type-I Heavy Tailed Weibull (TI-HTW) model
Wei Zhao +4 more
doaj +1 more source
On the Accuracy of Inference on Heavy-Tailed Distributions [PDF]
This paper suggests a simple method of deriving nonparametric lower bounds of the accuracy of statistical inference on heavy-tailed distributions. We present lower bounds of the mean squared error of the tail index, the tail constant, and extreme quantiles estimators. The results show that the normalizing sequences of robust estimators must depend in a
openaire +1 more source
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source
Interferon type 1 (IFN‐1) production and signaling is associated with the acquisition of therapy resistance, following chronic DNA damage, via Interferon‐related DNA damage resistance signature (IRDS) gene expression. An alternative, DNA damage‐independent role of sustained IFN‐1 mediated resistance was identified and characterized by the emergence of ...
Ashlyn Conant +11 more
wiley +1 more source
YIPFα1A expression is regulated by multilayered molecular mechanisms
YIPFα1A, a five‐pass Golgi protein, is regulated at multiple layers. (1) Rare‐codon enrichment drives translation‐coupled mRNA decay. (2) A proximal 3′‐UTR element stabilizes mRNA. (3) A distal 3′‐UTR element included by alternate poly(A) site usage represses translation, which can be overridden by the proximal 3′‐UTR element.
Tokio Takaji +2 more
wiley +1 more source

