Statistical Reasoning With Imprecise Probabilities
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Statistical Reasoning With Imprecise Probabilities
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Author : Peter Walley
language : en
Publisher: Chapman and Hall/CRC
Release Date : 1991
Statistical Reasoning With Imprecise Probabilities written by Peter Walley and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Mathematics categories.
An examination of topics involved in statistical reasoning with imprecise probabilities. The book discusses assessment and elicitation, extensions, envelopes and decisions, the importance of imprecision, conditional previsions and coherent statistical models.
Possibilistic Reasoning With Imprecise Probabilities Statistical Inference And Dynamic Filtering
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Author : Dominik Hose
language : en
Publisher:
Release Date : 2022
Possibilistic Reasoning With Imprecise Probabilities Statistical Inference And Dynamic Filtering written by Dominik Hose and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Statistical Reasoning
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Author : Gary Smith
language : en
Publisher: Allyn & Bacon
Release Date : 1991-01-01
Statistical Reasoning written by Gary Smith and has been published by Allyn & Bacon this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-01-01 with Probabilities categories.
The Geometry Of Uncertainty
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Author : Fabio Cuzzolin
language : en
Publisher: Springer Nature
Release Date : 2020-12-17
The Geometry Of Uncertainty written by Fabio Cuzzolin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-17 with Computers categories.
The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably complex geometric space, and manipulated in that space, for example, combined or conditioned. In the chapters in Part I, Theories of Uncertainty, the author offers an extensive recapitulation of the state of the art in the mathematics of uncertainty. This part of the book contains the most comprehensive summary to date of the whole of belief theory, with Chap. 4 outlining for the first time, and in a logical order, all the steps of the reasoning chain associated with modelling uncertainty using belief functions, in an attempt to provide a self-contained manual for the working scientist. In addition, the book proposes in Chap. 5 what is possibly the most detailed compendium available of all theories of uncertainty. Part II, The Geometry of Uncertainty, is the core of this book, as it introduces the author’s own geometric approach to uncertainty theory, starting with the geometry of belief functions: Chap. 7 studies the geometry of the space of belief functions, or belief space, both in terms of a simplex and in terms of its recursive bundle structure; Chap. 8 extends the analysis to Dempster’s rule of combination, introducing the notion of a conditional subspace and outlining a simple geometric construction for Dempster’s sum; Chap. 9 delves into the combinatorial properties of plausibility and commonality functions, as equivalent representations of the evidence carried by a belief function; then Chap. 10 starts extending the applicability of the geometric approach to other uncertainty measures, focusing in particular on possibility measures (consonant belief functions) and the related notion of a consistent belief function. The chapters in Part III, Geometric Interplays, are concerned with the interplay of uncertainty measures of different kinds, and the geometry of their relationship, with a particular focus on the approximation problem. Part IV, Geometric Reasoning, examines the application of the geometric approach to the various elements of the reasoning chain illustrated in Chap. 4, in particular conditioning and decision making. Part V concludes the book by outlining a future, complete statistical theory of random sets, future extensions of the geometric approach, and identifying high-impact applications to climate change, machine learning and artificial intelligence. The book is suitable for researchers in artificial intelligence, statistics, and applied science engaged with theories of uncertainty. The book is supported with the most comprehensive bibliography on belief and uncertainty theory.
Statistical Reasoning And Decision Making
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Author : Enders A. Robinson
language : en
Publisher:
Release Date : 1981
Statistical Reasoning And Decision Making written by Enders A. Robinson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Mathematics categories.
Improving Statistical Reasoning
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Author : Peter Sedlmeier
language : en
Publisher: Psychology Press
Release Date : 1999-06
Improving Statistical Reasoning written by Peter Sedlmeier and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-06 with Psychology categories.
This book describes an approach to understanding, modeling, and improving the probabilistic reasoning of ordinary adults, comparing their reasoning to that of "experts." For specialists in judgment and decision making and all cognitive scientists.
Statistical Reasoning
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Author : Smith
language : en
Publisher:
Release Date : 1991-08-01
Statistical Reasoning written by Smith and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-08-01 with categories.
Introduction To Imprecise Probabilities
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Author : Thomas Augustin
language : en
Publisher: John Wiley & Sons
Release Date : 2014-04-11
Introduction To Imprecise Probabilities written by Thomas Augustin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-11 with Mathematics categories.
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.
Uncertainty In Engineering
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Author : Louis J. M. Aslett
language : en
Publisher: Springer Nature
Release Date : 2022
Uncertainty In Engineering written by Louis J. M. Aslett and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.
Statistical Reasoning And Methods
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Author : Richard Arnold Johnson
language : en
Publisher:
Release Date : 2004
Statistical Reasoning And Methods written by Richard Arnold Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematical statistics categories.