Extremes最新文献_第5页

Large nearest neighbour balls in hyperbolic stochastic geometry 双曲随机几何中的大近邻球

IF 1.3 3区数学

Extremes Pub Date : 2022-09-26 DOI: 10.1007/s10687-023-00470-0

M. Otto, Christoph Thaele

引用次数: 3

Improved interexceedance-times-based estimator of the extremal index using truncated distribution 利用截断分布改进的基于间隔时间的极值指数估计方法

IF 1.3 3区数学

Extremes Pub Date : 2022-06-24 DOI: 10.1007/s10687-022-00444-8

Jan Holešovský, M. Fusek

引用次数: 4

A modeler’s guide to extreme value software 一个建模者的指南，极端价值的软件

IF 1.3 3区数学

Extremes Pub Date : 2022-05-16 DOI: 10.1007/s10687-023-00475-9

Léo R. Belzile, Christophe Dutang, P. Northrop, T. Opitz

引用次数: 3

Continuous simulation of storm processes 风暴过程的连续模拟

IF 1.3 3区数学

Extremes Pub Date : 2022-05-09 DOI: 10.1007/s10687-022-00438-6

Marine Demangeot, Rémi Carnec, E. Chautru, C. Lantuéjoul

引用次数: 0

Extremal characteristics of conditional models 条件模型的极值特征

IF 1.3 3区数学

Extremes Pub Date : 2022-02-23 DOI: 10.1007/s10687-022-00453-7

S. Tendijck, J. Tawn, P. Jonathan

引用次数: 0

Joint modeling and prediction of massive spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach 基于INLA-SPDE方法的大规模野火数量和燃烧面积的联合建模与预测

IF 1.3 3区数学

Extremes Pub Date : 2022-02-14 DOI: 10.1007/s10687-023-00463-z

Zhongwei Zhang, E. Krainski, P. Zhong, H. Rue, Raphael Huser

引用次数: 4

Reconstruction of incomplete wildfire data using deep generative models 使用深度生成模型重建不完整的野火数据

IF 1.3 3区数学

Extremes Pub Date : 2022-01-16 DOI: 10.1007/s10687-022-00459-1

T. Ivek, Domagoj Vlah

引用次数: 4

Regression-type analysis for multivariate extreme values. 多元极值的回归型分析。

IF 1.3 3区数学

Extremes Pub Date : 2022-01-01 Epub Date: 2022-10-21 DOI: 10.1007/s10687-022-00446-6

Miguel de Carvalho, Alina Kumukova, Gonçalo Dos Reis

{"title":"Regression-type analysis for multivariate extreme values.","authors":"Miguel de Carvalho, Alina Kumukova, Gonçalo Dos Reis","doi":"10.1007/s10687-022-00446-6","DOIUrl":"https://doi.org/10.1007/s10687-022-00446-6","url":null,"abstract":"This paper devises a regression-type model for the situation where both the response and covariates are extreme. The proposed approach is designed for the setting where the response and covariates are modeled as multivariate extreme values, and thus contrarily to standard regression methods it takes into account the key fact that the limiting distribution of suitably standardized componentwise maxima is an extreme value copula. An important target in the proposed framework is the regression manifold, which consists of a family of regression lines obeying the latter asymptotic result. To learn about the proposed model from data, we employ a Bernstein polynomial prior on the space of angular densities which leads to an induced prior on the space of regression manifolds. Numerical studies suggest a good performance of the proposed methods, and a finance real-data illustration reveals interesting aspects on the conditional risk of extreme losses in two leading international stock markets.Supplementary information: The online version contains supplementary material available at 10.1007/s10687-022-00446-6.","PeriodicalId":49274,"journal":{"name":"Extremes","volume":"25 4","pages":"595-622"},"PeriodicalIF":1.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589765/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40458093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Heavy-tailed phase-type distributions: a unified approach. 重尾相型分布:统一的方法。

IF 1.3 3区数学

Extremes Pub Date : 2022-01-01 Epub Date: 2022-02-16 DOI: 10.1007/s10687-022-00436-8

Martin Bladt, Jorge Yslas

{"title":"Heavy-tailed phase-type distributions: a unified approach.","authors":"Martin Bladt, Jorge Yslas","doi":"10.1007/s10687-022-00436-8","DOIUrl":"https://doi.org/10.1007/s10687-022-00436-8","url":null,"abstract":"A phase-type distribution is the distribution of the time until absorption in a finite state-space time-homogeneous Markov jump process, with one absorbing state and the rest being transient. These distributions are mathematically tractable and conceptually attractive to model physical phenomena due to their interpretation in terms of a hidden Markov structure. Three recent extensions of regular phase-type distributions give rise to models which allow for heavy tails: discrete- or continuous-scaling; fractional-time semi-Markov extensions; and inhomogeneous time-change of the underlying Markov process. In this paper, we present a unifying theory for heavy-tailed phase-type distributions for which all three approaches are particular cases. Our main objective is to provide useful models for heavy-tailed phase-type distributions, but any other tail behavior is also captured by our specification. We provide relevant new examples and also show how existing approaches are naturally embedded. Subsequently, two multivariate extensions are presented, inspired by the univariate construction which can be considered as a matrix version of a frailty model. We provide fully explicit EM-algorithms for all models and illustrate them using synthetic and real-life data.","PeriodicalId":49274,"journal":{"name":"Extremes","volume":"25 3","pages":"529-565"},"PeriodicalIF":1.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40568768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Tail processes and tail measures: An approach via Palm calculus 尾部过程和尾部度量：一种基于Palm演算的方法

IF 1.3 3区数学

Extremes Pub Date : 2021-12-31 DOI: 10.1007/s10687-023-00472-y

G. Last

引用次数: 4