Possibilistic Reasoning With Imprecise Probabilities Statistical Inference And Dynamic Filtering

Author : Dominik Hose
Publisher :
ISBN 13 : 9783844087215
Total Pages : 0 pages
Book Rating : 4.14/5 ( download)

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Download or read book Possibilistic Reasoning with Imprecise Probabilities: Statistical Inference and Dynamic Filtering written by Dominik Hose and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Sylvie Le Hégarat-Mascle
Publisher : Springer Nature
ISBN 13 : 3031178017
Total Pages : 318 pages
Book Rating : 4.16/5 ( download)

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Download or read book Belief Functions: Theory and Applications written by Sylvie Le Hégarat-Mascle and published by Springer Nature. This book was released on 2022-09-29 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition. The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.

Author : Peter Walley
Publisher : Springer
ISBN 13 : 9781489934734
Total Pages : 706 pages
Book Rating : 4.31/5 ( download)

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Download or read book Statistical Reasoning with Imprecise Probabilities written by Peter Walley and published by Springer. This book was released on with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: When I started writing this book, my mind was full of ignorance and uncertainty, particularly about how best to deal with ignorance and uncertainty. Much of the ignorance and uncertainty remains, now that the book is finished, but it is organized more coherently. I see that as progress. As the title indicates, the book is about methods of reasoning and statistical inference using imprecise probabilities. The methods are based on a behavioural interpretation of probability and principles of coherence. The idea for such a book originated in 1982, after I had written two long reports on the mathematics and elicitation of upper and lower probabilities. My experience in teaching and applying the existing theories of statistical inference had convinced me that each of them was inadequate. The Bayesian theory is inadequate, despite its great virtues of coherence, because it requires all probability assessments to be precise yet gives little guidance on how to make them. It seemed natural to investigate whether the Bayesian theory could be modified by admitting imprecise probabilities as models for partial ignorance. Is it possible to reconcile imprecision with coherence, vagueness with rationality? Fortunately the ans wer is yes! The basic ideas of the book appeared in the two technical reports (1981, 1982). The coherence principles for conditional probabilities and statistical models were worked out in New Zealand, in 1983.

Author : Ryan Martin
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781439886489
Total Pages : 0 pages
Book Rating : 4.82/5 ( download)

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Download or read book Inferential Models written by Ryan Martin and published by Chapman and Hall/CRC. This book was released on 2015-11-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delves into the authors’ work toward deeper understanding of statistical inference in terms of reasoning with uncertainty and meaningfulness of probabilistic inferential output. Focusing on a valid, prior-free probabilistic inferential framework called inferential models, the authors explain how to first identify the underlying source of uncertainty as an integral part of statistical modeling and then make probabilistic inference by calculating the predictable quantity in a statistically accurate way.

Author : Robert V. Hogg
Publisher :
ISBN 13 : 9789813026599
Total Pages : 731 pages
Book Rating : 4.96/5 ( download)

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Download or read book Probability and Statistical Inference written by Robert V. Hogg and published by . This book was released on 1996 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : John G. Kalbfleisch
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.73/5 ( download)

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Download or read book Probability and Statistical Inference written by John G. Kalbfleisch and published by . This book was released on 1979 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author :
Publisher :
ISBN 13 :
Total Pages : 1448 pages
Book Rating : 4.32/5 ( download)

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Download or read book Mathematical Reviews written by and published by . This book was released on 2003 with total page 1448 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Thomas Augustin
Publisher : John Wiley & Sons
ISBN 13 : 1118763149
Total Pages : 448 pages
Book Rating : 4.48/5 ( download)

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Download or read book Introduction to Imprecise Probabilities written by Thomas Augustin and published by John Wiley & Sons. This book was released on 2014-04-11 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the theory has become widely accepted and has beenfurther developed, but a detailed introduction is needed in orderto 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 appliedto many application areas. All authors of individual chapters areleading researchers on the specific topics, assuring high qualityand up-to-date contents. An Introduction to Imprecise Probabilities provides acomprehensive introduction to imprecise probabilities, includingtheory 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 ofimplementation (including elicitation and computation); Models infinance; Game-theoretic probability; Stochastic processes(including Markov chains); Engineering applications. Essential reading for researchers in academia, researchinstitutes and other organizations, as well as practitionersengaged in areas such as risk analysis and engineering.

Author : Laveen N. Kanal
Publisher : North Holland
ISBN 13 : 9780444700582
Total Pages : 509 pages
Book Rating : 4.87/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence written by Laveen N. Kanal and published by North Holland. This book was released on 1986 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardbound. How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

Author : Didier Dubois
Publisher : Springer Science & Business Media
ISBN 13 : 1461544297
Total Pages : 660 pages
Book Rating : 4.96/5 ( download)

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Download or read book Fundamentals of Fuzzy Sets written by Didier Dubois and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Fuzzy Sets covers the basic elements of fuzzy set theory. Its four-part organization provides easy referencing of recent as well as older results in the field. The first part discusses the historical emergence of fuzzy sets, and delves into fuzzy set connectives, and the representation and measurement of membership functions. The second part covers fuzzy relations, including orderings, similarity, and relational equations. The third part, devoted to uncertainty modelling, introduces possibility theory, contrasting and relating it with probabilities, and reviews information measures of specificity and fuzziness. The last part concerns fuzzy sets on the real line - computation with fuzzy intervals, metric topology of fuzzy numbers, and the calculus of fuzzy-valued functions. Each chapter is written by one or more recognized specialists and offers a tutorial introduction to the topics, together with an extensive bibliography.