000 02235nam a22002537a 4500
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020 _a9783030886578
082 _a519.542
_bLIO
100 _aLio, Yuhlon
_914440
245 _aBayesian inference and computation in reliability and survival analysis
260 _bSpringer
_aSwitzerland
_c2022
300 _axviii, 364 p.
365 _aEURO
_b129.99
490 _aEmerging Topics in Statistics and Biostatistics (ETSB)
520 _aBayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and engineering. In the past few decades, significant developments of Bayesian inference have been made by many researchers, and advancements in computational technology and computer performance has laid the groundwork for new opportunities in Bayesian computation for practitioners. Because these theoretical and technological developments introduce new questions and challenges, and increase the complexity of the Bayesian framework, this book brings together experts engaged in groundbreaking research on Bayesian inference and computation to discuss important issues, with emphasis on applications to reliability and survival analysis. Topics covered are timely and have the potential to influence the interacting worlds of biostatistics, engineering, medical sciences, statistics, and more. The included chapters present current methods, theories, and applications in the diverse area of biostatistical analysis. The volume as a whole serves as reference in driving quality global health research. (https://link.springer.com/book/10.1007/978-3-030-88658-5#about-this-book)
650 _aReliability (Engineering)
_916109
650 _aSurvival analysis (Biometry)
_916110
650 _aBayesian statistical decision theory
_915526
700 _aChen, Ding-Geng
_915045
700 _aTony Ng, Hon Keung
_916111
700 _aTsai, Tzong-Ru
_916112
942 _cBK
_2ddc
999 _c6189
_d6189