Notes on Robust Testing for Normality in Insurance Science

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F15%3A43906563" target="_blank" >RIV/62156489:43110/15:43906563 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fundacionmapfre.org/documentacion/publico/i18n/catalogo_imagenes/grupo.cmd?path=1083273" target="_blank" >https://www.fundacionmapfre.org/documentacion/publico/i18n/catalogo_imagenes/grupo.cmd?path=1083273</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Notes on Robust Testing for Normality in Insurance Science

Popis výsledku v původním jazyce

Insurance science is known as the discipline that applies mathematical and statistical methods. Within those, fitting of claims distribution is a very interesting and important issue. As it is generally known, the claim amounts to the insurance company can be usually described by several continuous non-negative random variables. Moreover, most insurance data is skewed to the right and therefore such probability distributions as exponential, log-normal, Weibull, Pareto, gamma and Burr distributions are usually used. The normal distribution is also important distribution used in insurance and risk management since it usually appears like limiting distribution in many cases. Similarly, many stochastic actuarial models, classical statistical tests and confidence intervals, widely used in insurance, require that the data has been generated by a normal distribution. Thus, the aim of this contribution is to present and discuss some interesting results of robust testing for normality with appl

Název v anglickém jazyce

Notes on Robust Testing for Normality in Insurance Science

Popis výsledku anglicky

Insurance science is known as the discipline that applies mathematical and statistical methods. Within those, fitting of claims distribution is a very interesting and important issue. As it is generally known, the claim amounts to the insurance company can be usually described by several continuous non-negative random variables. Moreover, most insurance data is skewed to the right and therefore such probability distributions as exponential, log-normal, Weibull, Pareto, gamma and Burr distributions are usually used. The normal distribution is also important distribution used in insurance and risk management since it usually appears like limiting distribution in many cases. Similarly, many stochastic actuarial models, classical statistical tests and confidence intervals, widely used in insurance, require that the data has been generated by a normal distribution. Thus, the aim of this contribution is to present and discuss some interesting results of robust testing for normality with appl

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Current Topics on Risk Analysis: ICRA6 and RISK 2015 Conference

ISBN

978-84-9844-496-4

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

749-756

Název nakladatele

Fundación Mapfre

Místo vydání

Madrid

Místo konání akce

Barcelona

Datum konání akce

26. 5. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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