Non-linear failure rate: A Bayes study using Hamiltonian Monte Carlo simulation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F20%3A00524681" target="_blank" >RIV/67985556:_____/20:00524681 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/20:10244936
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0888613X20301596" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0888613X20301596</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijar.2020.04.007" target="_blank" >10.1016/j.ijar.2020.04.007</a>
Alternative languages
Result language
angličtina
Original language name
Non-linear failure rate: A Bayes study using Hamiltonian Monte Carlo simulation
Original language description
A non-linear failure ratemodel is introduced, analyzed, and applied to real data sets for both censored and uncensored data. The Hamiltonian Monte Carlo and cross-entropy methods have been exploited to empower the traditional methods of statistical estimation. Bayes estimators of parameters and reliability characteristics uses the Hamiltonian Monte Carlo and these estimators are considered under both symmetric and asymmetric loss functions. Additionally, the maximum likelihood estimators of parameters are obtained by using the cross-entropy method to optimize the log-likelihood function. The superiority of the proposed model and estimation procedures are demonstrated on real data sets.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/EF16_019%2F0000867" target="_blank" >EF16_019/0000867: Research Centre of Advanced Mechatronic Systems</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Approximate Reasoning
ISSN
0888-613X
e-ISSN
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Volume of the periodical
123
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
22
Pages from-to
55-76
UT code for WoS article
000540209500005
EID of the result in the Scopus database
2-s2.0-85085638278