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extRemes 2.0: An Extreme Value Analysis Package in R [PDF]

open access: yesJournal of Statistical Software, 2016
This article describes the extreme value analysis (EVA) R package extRemes version 2.0, which is completely redesigned from previous versions. The functions primarily provide utilities for implementing univariate EVA, with a focus on weather and climate ...
Eric Gilleland, Richard W. Katz
doaj   +4 more sources

On Extreme Value Analysis of a Spatial Process

open access: greenRevstat Statistical Journal, 2008
One common way to deal with extreme value analysis in spatial statistics is by using the max-stable process. By employing a representation of simple max-stable processes in de Haan and Ferreira ([3]), we propose a stationary max-stable process as a ...
Laurens de Haan , Chen Zhou
doaj   +3 more sources

Extreme value analysis of the number of student absences in Jiangsu, China: Based on extreme value theory. [PDF]

open access: yesPLoS ONE
Attendance absences have a substantial impact on student's future physical and mental health as well as academic progress. Numerous personal, familial, and social issues are among the causes of student absences.
Mao Liu   +4 more
doaj   +4 more sources

The impacts of digital finance development on household income, consumption, and financial asset holding: an extreme value analysis of China's microdata. [PDF]

open access: yesPers Ubiquitous Comput, 2022
This paper examines the roles of digital finance development in household income, consumption, and financial asset holding from an extreme value theory perspective.
Lin H, Zhang Z.
europepmc   +2 more sources

Extreme-value analysis of teletra'c data [PDF]

open access: greenComputational Statistics & Data Analysis, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zoi Tsourti, John Panaretos
  +4 more sources

Extreme Value Analysis

open access: yesRevstat Statistical Journal, 2016
Extreme value theory is dedicated to characterise the behaviour of the extreme observations. The interest is then focused in the tails of the underlying distribution.
Helena Penalva   +2 more
doaj   +2 more sources

A generalized framework for process-informed nonstationary extreme value analysis

open access: bronzeAdvances in Water Resources, 2019
Evolving climate conditions and anthropogenic factors, such as CO2 emissions, urbanization and population growth, can cause changes in weather and climate extremes.
Elisa Ragno   +3 more
openalex   +3 more sources

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

open access: goldJournal of Marine Science and Engineering, 2021
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 zone and port defense structures.
Παναγιώτα Γαλιατσάτου   +3 more
openalex   +2 more sources

Bivariate extreme value analysis of extreme temperature and mortality in Canada, 2000-2020 [PDF]

open access: yesBMC Public Health
Climate change increases the risk of illness through rising temperature, severe precipitation and worst air pollution. This paper investigates how monthly excess mortality rate is associated with the increasing frequency and severity of extreme ...
Yuqing Zhang   +7 more
doaj   +2 more sources

Threshold selection in univariate extreme value analysis [PDF]

open access: yesExtremes, 2021
AbstractThreshold selection plays a key role in various aspects of statistical inference of rare events. In this work, two new threshold selection methods are introduced. The first approach measures the fit of the exponential approximation above a threshold and achieves good performance in small samples.
Schneider, Laura Fee   +5 more
openaire   +7 more sources

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