Analyzing relations of insured accident and selected risk factors with interactions

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F11%3A86079142" target="_blank" >RIV/61989100:27510/11:86079142 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Analyzing relations of insured accident and selected risk factors with interactions
Original language description
The paper is devoted to the analyzing impact of selected risk factors on insured accident and forecasting probability of loss occurrence. On the basis of these factors and measurement of their relation to the insured accident, it is possible to determinethe probability of insured accident for each policyholder and also to differentiate the paid insurance premiums in compliance with risk factors. The insurance premium is proposed in this way that it corresponds to undertaken risk, i.e. occurrence probability. In the purpose of identifying and modelling this relation, the logistic regression model is primarily employed, but potential interactions among factors during the proposing and estimating are often neglected. It results in the inaccurate parameter estimates and also in misinterpreting and incorrect assessing relation to the outcome generally. In the paper, the model with and without interaction is proposed and estimated and then, in compliance with both models, the relation of se
Czech name
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Czech description
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 29th International Conference on Mathematical Methods in Economics 2011 - part I
ISBN
978-80-7431-058-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
745-750
Publisher name
Professional Publishing
Place of publication
Prague
Event location
Janska Dolina
Event date
Sep 6, 2011
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000309074600124

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