Mixture failure rate: A study based on cross-entropy and MCMC method

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238402" target="_blank" >RIV/61989100:27240/17:10238402 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8024325" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8024325</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/DT.2017.8024325" target="_blank" >10.1109/DT.2017.8024325</a>

Result language
angličtina
Original language name
Mixture failure rate: A study based on cross-entropy and MCMC method
Original language description
In this paper, the parameters and reliability characteristics of the mixture of the failure time distribution are estimated based on a complete sample using both Markov Chain Monte Carlo (MCMC) method and maximum likelihood estimation via cross-entropy (CE) algorithm. While maximum likelihood estimation is the most frequently used method for parameter estimation, MCMC has recently emerged as a good alternative. The most popular MCMC method, called the Metropolis-Hastings algorithm, is used to provide a complete analysis of the concerned posterior distribution. A simulation study is provided to compare MCMC with CE, and differences between the estimates obtained by the two approaches are evaluated. © 2017 IEEE.
Czech name
—
Czech description
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Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the International Conference on Information and Digital Technologies, IDT 2017
ISBN
978-1-5090-5688-0
ISSN
—
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
373-382
Publisher name
IEEE
Place of publication
Piscataway
Event location
Žilina
Event date
Jul 5, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000426916900061

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