* The first book to chart the development and applications of this growing subject. * Provides a comprehensive introduction to imprecise probabilities, including theory and applications reflecting the current state of the art. * Each chapter is written by leading experts in their field. Editor(s): Augustin, Thomas; Coolen, Frank P. A.; de Cooman, Gert; Troffaes, Matthias C. M. Series: Wiley Series in Probability and Statistics. Num Pages: 448 pages, black & white illustrations, black & white tables, figures, graphs. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 179 x 245 x 26. Weight in Grams: 838. . 2014. 1st Edition. Hardcover. . . . .

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Bibliographic Details

Title: Introduction to Imprecise Probabilities
Publisher: John Wiley and Sons Ltd
Publication Date: 2014
Language: English
ISBN 10: 0470973811
ISBN 13: 9780470973813
Binding: Hardcover
Edition: 1st Edition
Condition: New

About this title

Synopsis

In recent years, the theory has become widely accepted and has been further developed, but a detailed introduction is needed in order to make the material available and accessible to a wide audience. This will be the first book providing such an introduction, covering core theory and recent developments which can be applied to many application areas. All authors of individual chapters are leading researchers on the specific topics, assuring high quality and up-to-date contents.

An Introduction to Imprecise Probabilities provides a comprehensive introduction to imprecise probabilities, including theory and applications reflecting the current state if the art. Each chapter is written by experts on the respective topics, including: Sets of desirable gambles; Coherent lower (conditional) previsions; Special cases and links to literature; Decision making; Graphical models; Classification; Reliability and risk assessment; Statistical inference; Structural judgments; Aspects of implementation (including elicitation and computation); Models in finance; Game-theoretic probability; Stochastic processes (including Markov chains); Engineering applications.

Essential reading for researchers in academia, research institutes and other organizations, as well as practitioners engaged in areas such as risk analysis and engineering.

About the Author

Thomas Augustin, Department of Statistics, University of Munich, Germany.

Frank Coolen, Department of Mathematical Sciences, Durham University, UK.

Gert de Cooman, Research Professor in Uncertainty Modelling and Systems Science, Ghent University, Belgium.

Matthias Troffaes, Department of Mathematical Sciences, Durham University, UK.

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