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, dynamic
reliability, 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.
Giới thiệu về tác giả
Nozer D. Singpurwalla is the author of Reliability and Risk: A Bayesian Perspective, published by Wiley.
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