This special volume of Statistical Sciences presents some innovative, if not
provocative, ideas in the area of reliability, or perhaps more appropriately
named, integrated system assessment. In this age of exponential growth in
science, engineering and technology, the capability to evaluate the
performance, reliability and safety of complex systems presents new challenges.
Today's methodology must respond to the ever-increasing demands for such
evaluations to provide key information for decision and policy makers at all
levels of government and industry--problems ranging from international security
to space exploration. We, the co-editors of this volume and the authors,
believe that scientific progress in reliability assessment requires the
development of processes, methods and tools that combine diverse information
types (e.g., experiments, computer simulations, expert knowledge) from diverse
sources (e.g., scientists, engineers, business developers, technology
integrators, decision makers) to assess quantitative performance metrics that
can aid decision making under uncertainty. These are highly interdisciplinary
problems. The principal role of statistical sciences is to bring statistical
rigor, thinking and methodology to these problems.Comment: Published at http://dx.doi.org/10.1214/088342306000000664 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org