"Reliability studies lead to problems of how to act and action is
best carried out by Bayesian principles. The author uses these to
provide a clear account of the subject that will be of value to
both theoreticians and practitioners."
--Dennis V. Lindley
"This is a wonderful book--well written, exceptionally
wide-ranging in its coverage of reliability and risk concepts and
applications, and coherently focused throughout by its Bayesian
perspective."
--Adrian F. M. Smith, Queen Mary, University of London, UK
"This groundbreaking book should be invaluable to those who wish
to understand reliability and survival analysis from the modern
Bayesian perspective."
--Joseph B. Kadane, Carnegie Mellon University, Pittsburgh,
USA
We all like to know how reliable and how risky certain
situations are, and our increasing reliance on technology has led
to the need for more precise assessments than ever before. Such
precision has resulted in efforts both to sharpen the notions of
risk and reliability, and to quantify them. Quantification is
required for normative decision-making, especially decisions
pertaining to our safety and wellbeing. Increasingly in recent
years Bayesian methods have become key to such quantifications.
"Reliability and Risk" provides a comprehensive overview of the
mathematical and statistical aspects of risk and reliability
analysis, from a Bayesian perspective. This book sets out to change
the way in which we think about reliability and survival analysis
by casting them in the broader context of decision-making. This is
achieved by:
Providing a broad coverage of the diverse aspects of
reliability, including: multivariate failure models,
dynamicreliability, event history analysis, non-parametric Bayes,
competing risks, co-operative and competing systems, and signature
analysis. Covering the essentials of Bayesian statistics and
exchangeability, enabling readers who are unfamiliar with Bayesian
inference to benefit from the book. Introducing the notion of
"composite reliability," or the collective reliability of a
population of items. Discussing the relationship between notions of
reliability and survival analysis and econometrics and financial
risk.
"Reliability and Risk" can most profitably be used by
practitioners and research workers in reliability and survivability
as a source of information, reference, and open problems. It can
also form the basis of a graduate level course in reliability and
risk analysis for students in statistics, biostatistics,
engineering (industrial, nuclear, systems), operations research,
and other mathematically oriented scientists, wherein the
instructor could supplement the material with examples and
problems.
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