Model Comparison and Quantification of Statistical Uncertainties for Annual Maxima of Ground Snow Loads

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21610%2F15%3A00234725" target="_blank" >RIV/68407700:21610/15:00234725 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Model Comparison and Quantification of Statistical Uncertainties for Annual Maxima of Ground Snow Loads

Popis výsledku v původním jazyce

This paper studies the effect of statistical uncertainties on fully probabilistic models and examines the current practice in civil engineering that typically neglects these uncertainties. Frequentist and Bayesian approaches are applied to quantify parameter estimation and model selection uncertainties. Focusing on annual maxima of ground snow loads, representative fractiles for different models and methods are compared. Four distribution types are considered and model uncertainty is accounted by modelaveraging. The numerical results indicate that for small to medium sample sizes the effect of statistical uncertainties can be substantial and should be accounted for in reliability studies. For three-parameter distributions the models without statistical uncertainty may underestimate the 1000-year return period fractiles by 20% compared to the models which incorporate this uncertainty. The Bayesian paradigm offers a coherent and rational way to incorporate statistical uncertainties.

Název v anglickém jazyce

Model Comparison and Quantification of Statistical Uncertainties for Annual Maxima of Ground Snow Loads

Popis výsledku anglicky

This paper studies the effect of statistical uncertainties on fully probabilistic models and examines the current practice in civil engineering that typically neglects these uncertainties. Frequentist and Bayesian approaches are applied to quantify parameter estimation and model selection uncertainties. Focusing on annual maxima of ground snow loads, representative fractiles for different models and methods are compared. Four distribution types are considered and model uncertainty is accounted by modelaveraging. The numerical results indicate that for small to medium sample sizes the effect of statistical uncertainties can be substantial and should be accounted for in reliability studies. For three-parameter distributions the models without statistical uncertainty may underestimate the 1000-year return period fractiles by 20% compared to the models which incorporate this uncertainty. The Bayesian paradigm offers a coherent and rational way to incorporate statistical uncertainties.

Druh

D - Stať ve sborníku

CEP obor

JN - Stavebnictví

OECD FORD obor

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Projekt

<a href="/cs/project/GBP105%2F12%2FG059" target="_blank" >GBP105/12/G059: Kumulativní časově závislé procesy ve stavebních materiálech a konstrukcích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Safety and Reliability of Complex Engineered Systems - Proceedings of the European Safety and Reliability Conference ESREL 2015

ISBN

978-1-138-02879-1

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

2667-2674

Název nakladatele

A. A. Balkema Publishers

Místo vydání

Leiden

Místo konání akce

Zürich

Datum konání akce

7. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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