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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • 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

  • 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