Download or read book Generalized Bayesian Inference Under Prior data Conflict written by Gero Walter and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Robust Bayesian Inference when the Data Conflicts with the Prior written by Thomas William Lucas and published by . This book was released on 1991 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Data Analysis Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Download or read book Information Processing and Management of Uncertainty in Knowledge Based Systems written by Joao Paulo Carvalho and published by Springer. This book was released on 2016-06-10 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set (CCIS 610 and 611) constitute the proceedings of the 16th International Conference on Information processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016, held in Eindhoven, The Netherlands, in June 2016. The 127 revised full papers presented together with four invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy measures and integrals; uncertainty quantification with imprecise probability; textual data processing; belief functions theory and its applications; graphical models; fuzzy implications functions; applications in medicine and bioinformatics; real-world applications; soft computing for image processing; clustering; fuzzy logic, formal concept analysis and rough sets; graded and many-valued modal logics; imperfect databases; multiple criteria decision methods; argumentation and belief revision; databases and information systems; conceptual aspects of data aggregation and complex data fusion; fuzzy sets and fuzzy logic; decision support; comparison measures; machine learning; social data processing; temporal data processing; aggregation.
Download or read book Bayesian Model Chekcing Prior data Conflict written by Hada Moshonov and published by . This book was released on 2007 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Imprecise Probabilities written by Thomas Augustin and published by John Wiley & Sons. This book was released on 2014-06-03 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Risk Reliability and Safety Innovating Theory and Practice written by Lesley Walls and published by CRC Press. This book was released on 2016-11-25 with total page 4767 pages. Available in PDF, EPUB and Kindle. Book excerpt: The safe and reliable performance of many systems with which we interact daily has been achieved through the analysis and management of risk. From complex infrastructures to consumer durables, from engineering systems and technologies used in transportation, health, energy, chemical, oil, gas, aerospace, maritime, defence and other sectors, the management of risk during design, manufacture, operation and decommissioning is vital. Methods and models to support risk-informed decision-making are well established but are continually challenged by technology innovations, increasing interdependencies, and changes in societal expectations. Risk, Reliability and Safety contains papers describing innovations in theory and practice contributed to the scientific programme of the European Safety and Reliability conference (ESREL 2016), held at the University of Strathclyde in Glasgow, Scotland (25—29 September 2016). Authors include scientists, academics, practitioners, regulators and other key individuals with expertise and experience relevant to specific areas. Papers include domain specific applications as well as general modelling methods. Papers cover evaluation of contemporary solutions, exploration of future challenges, and exposition of concepts, methods and processes. Topics include human factors, occupational health and safety, dynamic and systems reliability modelling, maintenance optimisation, uncertainty analysis, resilience assessment, risk and crisis management.
Download or read book Safety and Reliability of Complex Engineered Systems written by Luca Podofillini and published by CRC Press. This book was released on 2015-09-03 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: Safety and Reliability of Complex Engineered Systems contains the Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, held 7-10 September 2015 in Zurich, Switzerland. It includes about 570 papers accepted for presentation at the conference. These contributions focus on theories and methods in the area of risk, safety and
Download or read book Uncertainty in Engineering written by Louis J. M. Aslett and published by Springer Nature. This book was released on 2022 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Objective Bayesian Inference in General generalized Linear Mixed Models Using Reference Priors written by Xin Zhao and published by . This book was released on 2005 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Models for Discrete Longitudinal Data written by Geert Molenberghs and published by Springer Science & Business Media. This book was released on 2006-08-30 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.
Download or read book Symbolic and Quantitative Approaches to Reasoning with Uncertainty written by Gabriele Kern-Isberner and published by Springer Nature. This book was released on 2019-09-04 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2019, held in Belgrade, Serbia, in September 2019. The 41 full papers presented together with 3 abstracts of invited talks inn this volume were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections named: Argumentation; Belief Functions; Conditional, Default and Analogical Reasoning; Learning and Decision Making; Precise and Imprecise Probabilities; and Uncertain Reasoning for Applications.
Download or read book Statistical Modelling and Regression Structures written by Thomas Kneib and published by Springer Science & Business Media. This book was released on 2010-01-12 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributions collected in this book have been written by well-known statisticians to acknowledge Ludwig Fahrmeir's far-reaching impact on Statistics as a science, while celebrating his 65th birthday. The contributions cover broad areas of contemporary statistical model building, including semiparametric and geoadditive regression, Bayesian inference in complex regression models, time series modelling, statistical regularization, graphical models and stochastic volatility models.
Download or read book Bayesian Inference written by Rosario O. Cardenas and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Inference: Observations and Applications discusses standard Bayesian inference, in which a-priori distributions are standard probability distributions. In some cases, however, a more general form of a-priori distributions (fuzzy a-priori densities) is suitable to model a-priori information. The combination of fuzziness and stochastic uncertainty calls for a generalization of Bayesian inference, i.e. fuzzy Bayesian inference. The authors explain how Bayes theorem may be generalized to handle this situation. Next, they present a decision analytic framework for completing selection of optimal parameters for machining process definition. In addition, a discussion section on the subjects of inference, experimental design, and risk aversion is included. The concluding review focuses on the sparse Bayesian methods from their model specifications, interference algorithms, and applications in sensor array signal processing. Sparse and structured sparse Bayesian methods formulate problems in a probabilistic manner by constructing a hierarchical model, allowing for the obtainment of flexible modeling capability and statistical information. (Bayesian Inference: Observations and Applications discusses standard Bayesian inference, in which a-priori distributions are standard probability distributions. In some cases, however, a more general form of a-priori distributions (fuzzy a-priori densities) is suitable to model a-priori information. The combination of fuzziness and stochastic uncertainty calls for a generalization of Bayesian inference, i.e. fuzzy Bayesian inference. The authors explain how Bayes theorem may be generalized to handle this situation. Next, they present a decision analytic framework for completing selection of optimal parameters for machining process definition. In addition, a discussion section on the subjects of inference, experimental design, and risk aversion is included. The concluding review focuses on the sparse Bayesian methods from their model specifications, interference algorithms, and applications in sensor array signal processing. Sparse and structured sparse Bayesian methods formulate problems in a probabilistic manner by constructing a hierarchical model, allowing for the obtainment of flexible modeling capability and statistical information.
Download or read book Information Processing and Management of Uncertainty written by Anne Laurent and published by Springer. This book was released on 2014-07-17 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: These three volumes (CCIS 442, 443, 444) constitute the proceedings of the 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, held in Montpellier, France, July 15-19, 2014. The 180 revised full papers presented together with five invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on uncertainty and imprecision on the web of data; decision support and uncertainty management in agri-environment; fuzzy implications; clustering; fuzzy measures and integrals; non-classical logics; data analysis; real-world applications; aggregation; probabilistic networks; recommendation systems and social networks; fuzzy systems; fuzzy logic in boolean framework; management of uncertainty in social networks; from different to same, from imitation to analogy; soft computing and sensory analysis; database systems; fuzzy set theory; measurement and sensory information; aggregation; formal methods for vagueness and uncertainty in a many-valued realm; graduality; preferences; uncertainty management in machine learning; philosophy and history of soft computing; soft computing and sensory analysis; similarity analysis; fuzzy logic, formal concept analysis and rough set; intelligent databases and information systems; theory of evidence; aggregation functions; big data - the role of fuzzy methods; imprecise probabilities: from foundations to applications; multinomial logistic regression on Markov chains for crop rotation modelling; intelligent measurement and control for nonlinear systems.
Download or read book Bayesian Inference for Partially Identified Models written by Paul Gustafson and published by CRC Press. This book was released on 2015-04-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs. The book first describes how reparameterization can assist in computing posterior quantities and providing insight into the properties of Bayesian estimators. It next compares partial identification and model misspecification, discussing which is the lesser of the two evils. The author then works through PIM examples in depth, examining the ramifications of partial identification in terms of how inferences change and the extent to which they sharpen as more data accumulate. He also explains how to characterize the value of information obtained from data in a partially identified context and explores some recent applications of PIMs. In the final chapter, the author shares his thoughts on the past and present state of research on partial identification. This book helps readers understand how to use Bayesian methods for analyzing PIMs. Readers will recognize under what circumstances a posterior distribution on a target parameter will be usefully narrow versus uselessly wide.
Download or read book New Insights into Bayesian Inference written by Mohammad Saber Fallah Nezhad and published by BoD – Books on Demand. This book was released on 2018-05-02 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to the mathematical analysis of Bayesian decision-making when the state of the problem is unknown but further data about it can be obtained. The objective of such analysis is to determine the optimal decision or solution that is logically consistent with the preferences of the decision-maker, that can be analyzed using numerical utilities or criteria with the probabilities assigned to the possible state of the problem, such that these probabilities are updated by gathering new information.
