简介
"Tony Cox is among the most active and creative architects and users of quantitative risk analysis. This book is full of interesting equations, conceptual designs and conundrums that characterize QRA and its applications to risk management. Informed by trenchant thinking and perceptive writing, this is a timely resource for the risk analysis community." Michael R. Greenberg, Professor and Faculty Dean, Edward J. Bloustein School of Planning and Public Policy, Rutgers University "Tony Cox's impressive book applies both simple and cutting-edge risk models to a variety of fields. It demonstrates creative but tractable ways to model real-world problems of great practical importance regarding biological, engineering, and social risks. This book deserves to become influential and widely read by those seeking practical state-of-the-art methods for risk analysis." Vicki Bier, Professor, Engineering Physics and Industrial Engineering & Director - Center for Human Performance and Risk Analysis, University of Wisconsin-Madison "Risk analysis is as old as the first cave dweller mulling how to survive winter or woolly mammoths. It remains essential today in our world of accidents, disease, climate change and terrorism. But some say that quantitative risk analysis is too complicated or time-consuming, and that qualitative intuition is a better way to make decisions. In this ambitious and meticulous book, Tony Cox makes the case that quantitative risk analysis is actually the antidote to uncertainty and complexity, superior to other modes of thinking, both practical and effective. Cox raises the bar on a vital debate." Jonathan B. Wiener, Duke University, and President, Society for Risk Analysis (2008) "This is an excellent, approachable read for any risk manager. Simple but devastating examples show how not to do risk analysis. Insightful case studies apply quantitative risk assessment to natural, random threats, and to terrorist threats posed by an intelligent adversary. This is a timely and much-needed resource for skeptical consumers of risk analysis advice and products, and for those who need to improve upon current, dangerously simplistic, guidance on threat assessment and risk management." Gerald G. Brown, Distinguished Professor, Operations Research Department, Naval Postgraduate School, Monterey, CA "This book provides a refreshing new perspective on quantitative risk assessment, and should be of interest to a wide range of practitioners. Drawing substantially on his own work, Tony Cox demonstrates that QRA can be applied even to challenging and complex systems." Suresh Moolgavkar, Vice President and Principal Scientist, Exponent Scientific Consulting; Professor of Epidemiology, University of Washington
目录
Preface 6
Acknowledgments 14
Contents 18
Part I Introduction to Risk Analysis 28
Chapter 1 Quantitative Risk Assessment Goals and Challenges 29
Chapter 2 Introduction to Engineering Risk Analysis 60
Chapter 3 Introduction to Health Risk Analysis 98
Part II Avoiding Bad Risk Analysis 123
Chapter 4 Limitations of Risk Assessment Using Risk Matrices 124
Chapter 5 Limitations of Quantitative Risk Assessment Using Aggregate Exposure and Risk Models 148
Part III Principles for Doing Better 185
Chapter 6 Identifying Nonlinear Causal Relations in Large Data Sets 186
Chapter 7 Overcoming Preconceptions and Confirmation Biases Using Data Mining 200
Chapter 8 Estimating the Fraction of Disease Caused by One Component of a Complex Mixture: Bounds for Lung Cancer 224
Chapter 9 Bounding Resistance Risks for Penicillin 244
Chapter 10 Confronting Uncertain Causal Mechanisms - Portfolios of Possibilities 258
Chapter 11 Determining What Can Be Predicted: Identifiability 281
Part IV Applications and Extensions 301
Chapter 12 Predicting the Effects of Changes: Could Removing Arsenic from Tobacco Smoke Significantly Reduce Smoker Risks of Lung Cancer? 302
Chapter 13 Simplifying Complex Dynamic Networks: A Model of Protease Imbalance and COPD Dynamic Dose-Response 322
Chapter 14 Value of Information (VOI) in Risk Management Policies for Tracking and Testing Imported Cattle for BSE 343
Chapter 15 Improving Antiterrorism Risk Analysis 369
Chapter 16 Designing Resilient Telecommunications Networks 388
References 408
Index 440
Acknowledgments 14
Contents 18
Part I Introduction to Risk Analysis 28
Chapter 1 Quantitative Risk Assessment Goals and Challenges 29
Chapter 2 Introduction to Engineering Risk Analysis 60
Chapter 3 Introduction to Health Risk Analysis 98
Part II Avoiding Bad Risk Analysis 123
Chapter 4 Limitations of Risk Assessment Using Risk Matrices 124
Chapter 5 Limitations of Quantitative Risk Assessment Using Aggregate Exposure and Risk Models 148
Part III Principles for Doing Better 185
Chapter 6 Identifying Nonlinear Causal Relations in Large Data Sets 186
Chapter 7 Overcoming Preconceptions and Confirmation Biases Using Data Mining 200
Chapter 8 Estimating the Fraction of Disease Caused by One Component of a Complex Mixture: Bounds for Lung Cancer 224
Chapter 9 Bounding Resistance Risks for Penicillin 244
Chapter 10 Confronting Uncertain Causal Mechanisms - Portfolios of Possibilities 258
Chapter 11 Determining What Can Be Predicted: Identifiability 281
Part IV Applications and Extensions 301
Chapter 12 Predicting the Effects of Changes: Could Removing Arsenic from Tobacco Smoke Significantly Reduce Smoker Risks of Lung Cancer? 302
Chapter 13 Simplifying Complex Dynamic Networks: A Model of Protease Imbalance and COPD Dynamic Dose-Response 322
Chapter 14 Value of Information (VOI) in Risk Management Policies for Tracking and Testing Imported Cattle for BSE 343
Chapter 15 Improving Antiterrorism Risk Analysis 369
Chapter 16 Designing Resilient Telecommunications Networks 388
References 408
Index 440
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