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In establishing a framework for dealing with uncertainties in software engineering, and for using quantitative measures in related decision-making, this text puts into perspective the large body of work having statistical content that is relevant to software engineering. Aimed at computer scientists, software engineers, and reliability analysts who have some exposure to probability and statistics, the content is pitched at a level appropriate for research workers in software reliability, and for graduate level courses in applied statistics computer science, operations research, and software engineering.
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Analytical and Computational Methods in Probability Theory - First International Conference, ACMPT 2017, Moscow, Russia, October 23-27, 2017, Proceedings (Paperback, 1st ed. 2017)
Vladimir V. Rykov, Nozer D Singpurwalla, Andrey M. Zubkov
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Discovery Miles 16 390
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the First
International Conference on Analytical and Computational Methods in
Probability Theory and its Applications, ACMPT 2017, held in
Moscow, Russia, in October 2017. The 42 full papers presented were
carefully reviewed and selected from 173 submissions. The
conference program consisted of four main themes associated with
significant contributions made by A.D.Soloviev. These are:
Analytical methods in probability theory, Computational methods in
probability theory, Asymptotical methods in probability theory, the
history of mathematics.
In establishing a framework for dealing with uncertainties in
software engineering, and for using quantitative measures in
related decision-making, this text puts into perspective the large
body of work having statistical content that is relevant to
software engineering. Aimed at computer scientists, software
engineers, and reliability analysts who have some exposure to
probability and statistics, the content is pitched at a level
appropriate for research workers in software reliability, and for
graduate level courses in applied statistics computer science,
operations research, and software engineering.
This third volume of case studies presents detailed applications of
Bayesian statistical analysis, emphasising the scientific context.
The papers were presented and discussed at a workshop held at
Carnegie-Mellon University, and this volume - dedicated to the
memory of Morrie Groot-reproduces six invited papers, each with
accompanying invited discussion, and nine contributed papers with
the focus on econometric applications.
Like its predecessor, this second volume presents detailed
applications of Bayesian statistical analysis, each of which
emphasizes the scientific context of the problems it attempts to
solve. The emphasis of this volume is on biomedical applications.
These papers were presented at a workshop at Carnegie-Mellon
University in 1993.
The past few years have witnessed dramatic advances in
computational methods for Bayesian inference. As a result, Bayesian
approaches to solving a wide variety of problems in data analysis
and decision-making have become feasible, and there is currently a
growth spurt in the application of Bayesian methods. The purpose of
this volume is to present several detailed examples of applications
of Bayesian thinking, with an emphasis on the scientific or
technological context of the problem being solved. The papers
collected here were presented and discussed at a Workshop held at
Carnegie-Mellon University, September 29 through October 1, 1991.
There are five ma jor articles, each with two discussion pieces and
a reply. These articles were invited by us following a public
solicitation of abstracts. The problems they address are diverse,
but all bear on policy decision-making. Though not part of our
original design for the Workshop, that commonality of theme does
emphasize the usefulness of Bayesian meth ods in this arena. Along
with the invited papers were several additional commentaries of a
general nature; the first comment was invited and the remainder
grew out of the discussion at the Workshop. In addition there are
nine contributed papers, selected from the thirty-four presented at
the Workshop, on a variety of applications. This collection of case
studies illustrates the ways in which Bayesian methods are being
incorporated into statistical practice. The strengths (and
limitations) of the approach become apparent through the examples."
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