• Mathematics

Risk Assessment and Decision Analysis with Bayesian Networks, Second Edition


Author: Norman Fenton,Martin Neil
Publisher: CRC Press
ISBN: 1351978969
Category: Mathematics
Page: 704
View: 1108
Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

    • Business & Economics

Risk Assessment and Decision Analysis with Bayesian Networks


Author: Norman Fenton,Martin Neil
Publisher: CRC Press
ISBN: 1439809119
Category: Business & Economics
Page: 524
View: 5446
Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.

    • Business & Economics

Risk Assessment and Decision Analysis with Bayesian Networks


Author: Norman Fenton,Martin Neil
Publisher: CRC Press
ISBN: 1439809100
Category: Business & Economics
Page: 524
View: 8748
Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.

    • Mathematics

Bayesian Networks and Decision Graphs


Author: Thomas Dyhre Nielsen,FINN VERNER JENSEN
Publisher: Springer Science & Business Media
ISBN: 1475735022
Category: Mathematics
Page: 268
View: 9117
Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and understand them, and when communicated to a computer, they can easily be compiled. The book emphasizes both the human and the computer side. It gives a thorough introduction to Bayesian networks, decision trees and influence diagrams as well as algorithms and complexity issues.

    • Mathematics

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science


Author: Franco Taroni,Alex Biedermann,Silvia Bozza,Paolo Garbolino,Colin Aitken
Publisher: John Wiley & Sons
ISBN: 1118914740
Category: Mathematics
Page: 472
View: 9358
"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation" Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. • Includes self-contained introductions to probability and decision theory. • Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. • Features implementation of the methodology with reference to commercial and academically available software. • Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. • Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. • Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. • Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. • Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

    • Business & Economics

Coherent Stress Testing

A Bayesian Approach to the Analysis of Financial Stress
Author: Riccardo Rebonato
Publisher: John Wiley & Sons
ISBN: 0470971487
Category: Business & Economics
Page: 238
View: 2693
In Coherent Stress Testing: A Bayesian Approach, industry expert Riccardo Rebonato presents a groundbreaking new approach to this important but often undervalued part of the risk management toolkit. Based on the author's extensive work, research and presentations in the area, the book fills a gap in quantitative risk management by introducing a new and very intuitively appealing approach to stress testing based on expert judgement and Bayesian networks. It constitutes a radical departure from the traditional statistical methodologies based on Economic Capital or Extreme-Value-Theory approaches. The book is split into four parts. Part I looks at stress testing and at its role in modern risk management. It discusses the distinctions between risk and uncertainty, the different types of probability that are used in risk management today and for which tasks they are best used. Stress testing is positioned as a bridge between the statistical areas where VaR can be effective and the domain of total Keynesian uncertainty. Part II lays down the quantitative foundations for the concepts described in the rest of the book. Part III takes readers through the application of the tools discussed in part II, and introduces two different systematic approaches to obtaining a coherent stress testing output that can satisfy the needs of industry users and regulators. In part IV the author addresses more practical questions such as embedding the suggestions of the book into a viable governance structure.

    • Mathematics

Bayesian Networks

A Practical Guide to Applications
Author: Olivier Pourret,Patrick Naïm,Bruce Marcot
Publisher: John Wiley & Sons
ISBN: 9780470994542
Category: Mathematics
Page: 446
View: 7847
Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

    • Business & Economics

Adversarial Risk Analysis


Author: David L. Banks,Jesus M. Rios Aliaga,David Rios Insua
Publisher: CRC Press
ISBN: 1498712401
Category: Business & Economics
Page: 224
View: 2952
Flexible Models to Analyze Opponent Behavior A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. The book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent’s goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities.

    • Computers

Bayesian Networks

With Examples in R
Author: Marco Scutari,Jean-Baptiste Denis
Publisher: CRC Press
ISBN: 1482225581
Category: Computers
Page: 241
View: 6522
Understand the Foundations of Bayesian Networks—Core Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the simplest notions and gradually increase in complexity. The authors also distinguish the probabilistic models from their estimation with data sets. The first three chapters explain the whole process of Bayesian network modeling, from structure learning to parameter learning to inference. These chapters cover discrete Bayesian, Gaussian Bayesian, and hybrid networks, including arbitrary random variables. The book then gives a concise but rigorous treatment of the fundamentals of Bayesian networks and offers an introduction to causal Bayesian networks. It also presents an overview of R and other software packages appropriate for Bayesian networks. The final chapter evaluates two real-world examples: a landmark causal protein signaling network paper and graphical modeling approaches for predicting the composition of different body parts. Suitable for graduate students and non-statisticians, this text provides an introductory overview of Bayesian networks. It gives readers a clear, practical understanding of the general approach and steps involved.

    • Computers

Modeling and Reasoning with Bayesian Networks


Author: Adnan Darwiche
Publisher: Cambridge University Press
ISBN: 0521884381
Category: Computers
Page: 548
View: 6551
This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.

    • Business & Economics

Risk Modeling, Assessment, and Management


Author: Yacov Y. Haimes
Publisher: John Wiley & Sons
ISBN: 1119017998
Category: Business & Economics
Page: 720
View: 9627
Presents systems-based theory, methodology, and applications in risk modeling, assessment, and management This book examines risk analysis, focusing on quantifying risk and constructing probabilities for real-world decision-making, including engineering, design, technology, institutions, organizations, and policy. The author presents fundamental concepts (hierarchical holographic modeling; state space; decision analysis; multi-objective trade-off analysis) as well as advanced material (extreme events and the partitioned multi-objective risk method; multi-objective decision trees; multi-objective risk impact analysis method; guiding principles in risk analysis); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies. The book will be used in systems engineering, enterprise risk management, engineering management, industrial engineering, civil engineering, and operations research. The fourth edition of Risk Modeling, Assessment, and Management features: Expanded chapters on systems-based guiding principles for risk modeling, planning, assessment, management, and communication; modeling interdependent and interconnected complex systems of systems with phantom system models; and hierarchical holographic modeling An expanded appendix including a Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmer’s Dilemma formulated and solved using a deterministic linear model Updated case studies including a new case study on sequential Pareto-optimal decisions for emergent complex systems of systems A new companion website with over 200 solved exercises that feature risk analysis theories, methodologies, and application Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.

    • Technology & Engineering

Risk Assessment

Tools, Techniques, and Their Applications
Author: Lee T. Ostrom,Cheryl A. Wilhelmsen
Publisher: John Wiley & Sons
ISBN: 1118309634
Category: Technology & Engineering
Page: 416
View: 5627
All the tools needed to perform a thorough risk assessment—whether you're working in insurance, forensics, engineering, or public safety Risk analysis is the method of analyzing the dangers to individuals, businesses, and government agencies posed by potential natural and man-made hazards. The central task of the risk assessor is predicting the success of a project. This includes isolating the entire spectrum of adverse events that can derail a project or threaten the health and safety of individuals, organizations, and the environment. Designed as a practical, in-the-field toolkit, Risk Assessment details every aspect of how a risk assessment is performed, showing the proper tool to be used at various steps in the process, as well as locating the tool that best fits the risk assessment task at hand. Examining not only the very nature of risks and consequences, with fascinating historical examples, the book progresses from simple to more complex risk assessment techniques used by the authors in their daily work, all presented in a form that can be readily adapted to any number of real-life situations: Ecological Risk Assessment Task Analysis Techniques Preliminary Hazards Analysis Failure Mode and Effects Analysis Human Reliability Analysis Critical Incident Technique With numerous industry-specific case studies, as well as additional case studies for risk assessments for a restaurant and a process plant, the book provides readers with complete examples of how each of the techniques can be used in a variety of real-world situations. Including downloadable worksheets and other useful assessment materials, as well as guidance on using PRA software, this unparalleled reference offers all the tools and techniques needed to conduct a thorough and accurate assessment of risk.

    • Business & Economics

Bayesian Artificial Intelligence, Second Edition


Author: Kevin B. Korb,Ann E. Nicholson
Publisher: CRC Press
ISBN: 1439815925
Category: Business & Economics
Page: 491
View: 4409
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology. New to the Second Edition New chapter on Bayesian network classifiers New section on object-oriented Bayesian networks New section that addresses foundational problems with causal discovery and Markov blanket discovery New section that covers methods of evaluating causal discovery programs Discussions of many common modeling errors New applications and case studies More coverage on the uses of causal interventions to understand and reason with causal Bayesian networks Illustrated with real case studies, the second edition of this bestseller continues to cover the groundwork of Bayesian networks. It presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop probabilistic expert systems. Web Resource The book’s website at www.csse.monash.edu.au/bai/book/book.html offers a variety of supplemental materials, including example Bayesian networks and data sets. Instructors can email the authors for sample solutions to many of the problems in the text.

    • Business & Economics

Portfolio Management under Stress

A Bayesian-Net Approach to Coherent Asset Allocation
Author: Riccardo Rebonato,Alexander Denev
Publisher: Cambridge University Press
ISBN: 1107048117
Category: Business & Economics
Page: 516
View: 5900
A rigorous presentation of a novel methodology for asset allocation in financial portfolios under conditions of market distress.

    • Computers

Software Metrics

A Rigorous and Practical Approach, Third Edition
Author: Norman Fenton,James Bieman
Publisher: CRC Press
ISBN: 1439838232
Category: Computers
Page: 617
View: 6478
A Framework for Managing, Measuring, and Predicting Attributes of Software Development Products and Processes Reflecting the immense progress in the development and use of software metrics in the past decades, Software Metrics: A Rigorous and Practical Approach, Third Edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. Like its popular predecessors, this third edition discusses important issues, explains essential concepts, and offers new approaches for tackling long-standing problems. New to the Third Edition This edition contains new material relevant to object-oriented design, design patterns, model-driven development, and agile development processes. It includes a new chapter on causal models and Bayesian networks and their application to software engineering. This edition also incorporates recent references to the latest software metrics activities, including research results, industrial case studies, and standards. Suitable for a Range of Readers With numerous examples and exercises, this book continues to serve a wide audience. It can be used as a textbook for a software metrics and quality assurance course or as a useful supplement in any software engineering course. Practitioners will appreciate the important results that have previously only appeared in research-oriented publications. Researchers will welcome the material on new results as well as the extensive bibliography of measurement-related information. The book also gives software managers and developers practical guidelines for selecting metrics and planning their use in a measurement program.

    • Business & Economics

Risk Assessment

A Practical Guide to Assessing Operational Risks
Author: Georgi Popov,Bruce K. Lyon,Bruce Hollcroft
Publisher: John Wiley & Sons
ISBN: 1118911040
Category: Business & Economics
Page: 480
View: 2836
Covers the fundamentals of risk assessment and emphasizes taking a practical approach in the application of the techniques Written as a primer for students and employed safety professionals covering the fundamentals of risk assessment and emphasizing a practical approach in the application of the techniques Each chapter is developed as a stand-alone essay, making it easier to cover a subject Includes interactive exercises, links, videos, and downloadable risk assessment tools Addresses criteria prescribed by the Accreditation Board for Engineering and Technology (ABET) for safety programs

    • Technology & Engineering

Guidelines for Fire Protection in Chemical, Petrochemical, and Hydrocarbon Processing Facilities


Author: Center for Chemical Process Safety (CCPS)
Publisher: Wiley-AIChE
ISBN: 9780816908981
Category: Technology & Engineering
Page: 480
View: 5169
While there are many resources available on fire protection and prevention in chemical petrochemical and petroleum plants—this is the first book that pulls them all together in one comprehensive resource. This book provides the tools to develop, implement, and integrate a fire protection program into a company or facility’s Risk Management System. This definitive volume is a must-read for loss prevention managers, site managers, project managers, engineers and EHS professionals. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

    • Business & Economics

Risk Analysis

A Quantitative Guide
Author: David Vose
Publisher: John Wiley & Sons
ISBN: 0470512849
Category: Business & Economics
Page: 752
View: 7576
Risk Analysis concerns itself with the quantification of risk, the modeling of identified risks and how to make decisions from those models. Quantitative risk analysis (QRA) using Monte Carlo simulation offers a powerful and precise method for dealing with the uncertainty and variability of a problem. By providing the building blocks the author guides the reader through the necessary steps to produce an accurate risk analysis model and offers general and specific techniques to cope with most modeling problems. A wide range of solved problems is used to illustrate these techniques and how they can be used together to solve otherwise complex problems.