When Things Get Extreme: Records and Crashes

Werner Müller; Andreas Quatember; Helmut Waldl

doi:10.1007/978-3-031-69111-9_21

When Things Get Extreme: Records and Crashes

Werner Müller, Andreas Quatember, Helmut Waldl

Department of Data Acquisition and Data Quality

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This contribution is concerned with statistical methods for analyzing extremes in univariate and multivariate time series. In particular, we discuss their use for the detection of global warming signals and assessing dependencies that typically arise in risk management. Multiple connections to the oeuvre of Wolfgang Schmid are indicated (The text is a translated, edited, expanded, and updated version of (Müller and Quatember, Wenn es extrem wird: Krachende Rekorde. In W. G. Müller, A. Quatember (Eds.), Fakt oder Fake? Wie Ihnen Statistik bei der Unterscheidung helfen kann (pp 149–161). Springer, 2022) by permission through Springer Nature license #5420800249333.).

Original language	English
Title of host publication	Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science Essays in Honour of Wolfgang Schmid
Editors	Sven Knoth, Yarema Okhrin, Philipp Otto
Publisher	Springer
Pages	441-448
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-031-69111-9_21
Publication status	Published - 2024

Fields of science

101018 Statistics
101026 Time series analysis
105108 Geostatistics
509 Other Social Sciences

JKU Focus areas

Sustainable Development: Responsible Technologies and Management

Access to Document

10.1007/978-3-031-69111-9_21

Statistical Literacy
Bitto-Nemling, A. (Researcher), Chen, H. (Researcher), Duller, C. (Researcher), Futschik, A. (Researcher), Hainy, M. (Researcher), Müller, W. (Researcher), Stadler, A. (Researcher), Tubikanec, I. (Researcher), Wagner, H. (Researcher), Waldl, H. (Researcher) & Quatember, A. (PI)
01.01.2019 → 31.12.2025
Project: Other › Project from scientific scope of research unit
Spatial econometrics
Waldl, H. (Researcher) & Müller, W. (PI)
01.01.2012 → 31.12.2025
Project: Other › Project from scientific scope of research unit
Applications of Statistical Methods
Bitto-Nemling, A. (Researcher), Futschik, A. (Researcher), Hainy, M. (Researcher), Müller, W. (Researcher), Quatember, A. (Researcher), Tubikanec, I. (Researcher), Wagner, H. (Researcher), Waldl, H. (Researcher) & Duller, C. (PI)
01.01.2012 → 31.12.2032
Project: Other › Project from scientific scope of research unit

Cite this

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title = "When Things Get Extreme: Records and Crashes",

abstract = "This contribution is concerned with statistical methods for analyzing extremes in univariate and multivariate time series. In particular, we discuss their use for the detection of global warming signals and assessing dependencies that typically arise in risk management. Multiple connections to the oeuvre of Wolfgang Schmid are indicated (The text is a translated, edited, expanded, and updated version of (M{\"u}ller and Quatember, Wenn es extrem wird: Krachende Rekorde. In W. G. M{\"u}ller, A. Quatember (Eds.), Fakt oder Fake? Wie Ihnen Statistik bei der Unterscheidung helfen kann (pp 149–161). Springer, 2022) by permission through Springer Nature license #5420800249333.).",

author = "Werner M{\"u}ller and Andreas Quatember and Helmut Waldl",

year = "2024",

doi = "10.1007/978-3-031-69111-9_21",

language = "English",

pages = "441--448",

editor = "{Sven Knoth, Yarema Okhrin, Philipp Otto}",

booktitle = "Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science Essays in Honour of Wolfgang Schmid",

publisher = "Springer",

}

When Things Get Extreme: Records and Crashes. / Müller, Werner ; Quatember, Andreas ; Waldl, Helmut.
Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science Essays in Honour of Wolfgang Schmid. ed. / Sven Knoth, Yarema Okhrin, Philipp Otto. Springer, 2024. p. 441-448.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Quatember, Andreas

AU - Waldl, Helmut

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AB - This contribution is concerned with statistical methods for analyzing extremes in univariate and multivariate time series. In particular, we discuss their use for the detection of global warming signals and assessing dependencies that typically arise in risk management. Multiple connections to the oeuvre of Wolfgang Schmid are indicated (The text is a translated, edited, expanded, and updated version of (Müller and Quatember, Wenn es extrem wird: Krachende Rekorde. In W. G. Müller, A. Quatember (Eds.), Fakt oder Fake? Wie Ihnen Statistik bei der Unterscheidung helfen kann (pp 149–161). Springer, 2022) by permission through Springer Nature license #5420800249333.).

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A2 - Sven Knoth, Yarema Okhrin, Philipp Otto, null

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ER -

When Things Get Extreme: Records and Crashes

Abstract

Fields of science

JKU Focus areas

Access to Document

Projects

Statistical Literacy

Spatial econometrics

Applications of Statistical Methods

Cite this