Bayesian 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.