BAYESIAN ESTIMATES OF PROBABILITY OF INCIDENCES AND MORTALITIES OF SELECTED SERIOUS DISEASES
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F18%3A39912700" target="_blank" >RIV/00216275:25410/18:39912700 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
BAYESIAN ESTIMATES OF PROBABILITY OF INCIDENCES AND MORTALITIES OF SELECTED SERIOUS DISEASES
Original language description
Oncological diseases are really serious, because they are already occurring in childhood and their number is growing rapidly. This problem is very dangerous not only for the European population, but also for the population all over the world. The Bayesian theory of credibility, in particular the binomial/beta model, can be appropriate method to determine the probability of incidences and mortalities, especially in cases of insurance companies. The main aim of this article is to evaluate these probabilities using the binomial/beta model and compare the advantages of Bayesian estimates to the maximum likelihood estimations based on trachea, bronchus and lung cancers in the Czech Republic and Ukraine. Data are obtained from the databases of WHO and OECD.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Herald of LUTE. Technical Sciences
ISSN
2522-1221
e-ISSN
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Volume of the periodical
2018
Issue of the periodical within the volume
54
Country of publishing house
UA - UKRAINE
Number of pages
7
Pages from-to
59-65
UT code for WoS article
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EID of the result in the Scopus database
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