Foundations of Risk Analysis Second Edition 风险分析基础

Contents
Preface to the second edition ix
# w  \* ?& t+ g3 u- PPreface to the first edition xi
1 Introduction 1
1.1 The importance of risk and uncertainty assessments 1
  \; Z- J4 `4 q" `+ m1.2 The need to develop a proper risk analysis framework 4
Bibliographic notes 6
2 Common thinking about risk and risk analysis 7
2.1 Accident risk 7
) w' b, g' l1 b- `5 m2.1.1 Accident statistics 7
; ]6 E, t9 L- G" q: _. T2.1.2 Risk analysis 11
5 T. }* f- G0 }5 g; e5 ~2.1.3 Reliability analysis 24
5 i5 @/ N5 r3 F3 N# L: r2.2 Economic risk 28
* l6 N- A* [' {6 D2.2.1 General definitions of economic risk in business and project
management 28
" @) D& g4 i  V; O* P8 j, N2 C2.2.2 A cost risk analysis 30
/ ]# k4 l: g; u+ B5 {. P* ~2.2.3 Finance and portfolio theory 31
" Y* ?( a4 ?/ N  J) Q2.2.4 Treatment of risk in project discounted cash flow analysis 34
3 H; K$ Q" i- e( Z& l+ w2.3 Discussion and conclusions 36
2.3.1 The classical approach 36
7 p* C' Y* |$ B* |* _2.3.2 The Bayesian paradigm 37
, I: l  ~/ R: g* P. x: v5 C2.3.3 Economic risk and rational decision-making 39
2.3.4 Other perspectives and applications 40
9 l  `7 }  _/ F  w2.3.5 Conclusions 43
3 h; d* x+ N5 l) n( o- g9 cBibliographic notes 43
3 How to think about risk and risk analysis 47
3.1 Basic ideas and principles 47
& R2 A# g% I4 b4 N) ~3.1.1 Background knowledge 52
3.1.2 Models and simplifications in probability considerations 53
+ B$ m' D" k$ e1 \0 v3.1.3 Observable quantities 53
7 G/ `* r# B/ w3.2 Economic risk 54
3.2.1 A simple cost risk example 54
% i4 ^. E. w, v; c3.2.2 Production risk 57
$ @* G3 }- L3 J3.2.3 Business and project management 59
vi CONTENTS
3.2.4 Investing money in a stock market 60
& H' w( Z7 d1 U( W' {( w3.2.5 Discounted cash flow analysis 61
5 e7 e- _+ T. g' G4 w$ r, T3.3 Accident risk 62
3.4 Discussion 63
Bibliographic notes 68
4 How to assess uncertainties and specify probabilities 71
4.1 What is a good probability assignment? 72
4.1.1 Criteria for evaluating probabilities 72
) _, r% l/ M' o3 E( f3 [7 H; F# t4.1.2 Heuristics and biases 74
4.1.3 Evaluation of the assessors 75
4.1.4 Standardization and consensus 76
3 P' v2 q* ~, X3 ]7 P; I" A: }1 \% n4.2 Modeling 76
4.2.1 Examples of models 77
) ^9 T, x; {* Q  ?: f6 D, y4.2.2 Discussion 78
' C7 H. N! P8 O3 y; z4.3 Assessing uncertainty of Y 79
4.3.1 Assignments based on classical statistical methods 80
- R8 {6 ^; H; {  A- q) ?- N6 C4.3.2 Analyst judgments using all sources of information 81
' \. e, ?( O! T" S4 ?0 N2 W: }) i4.3.3 Formal expert elicitation 82
9 O& L& e* O4 T5 X. t& k1 o" e4.3.4 Bayesian analysis 83
6 A) Q( j8 Q6 C! c$ {( B% ~4.4 Uncertainty assessments of a vector X 91
4.4.1 Cost risk 91
4.4.2 Production risk 93
4.4.3 Reliability analysis 94
) A4 K8 w7 @& \3 o( j3 A$ b4.5 Discussion 97
" T8 ]3 z, z' [& z# m: X1 b4.5.1 Risk analysis and science 97
6 o) C/ V# [2 ~, M0 C4.5.2 Probability and utility 98
. y- z" B( z: i" o# j4.5.3 Probability and knowledge 99
4.5.4 Probability models 99
4.5.5 Firm and vague probabilities 100
4.5.6 The need for seeing beyond probabilities 100
4.5.7 Interval (imprecise) probabilities 101
) ~+ V) F  [$ h0 K2 N4 v4.5.8 Example of interval (imprecise) probabilities in a risk analysis
setting 102
* R  V6 _0 J( @: V4.5.9 Possibility theory 103
4.5.10 Example of interval (imprecise) probabilities in a risk analysis
6 y- Y, X  q2 G8 n2 ^context using possibility theory 104
$ ~3 f4 ~5 V' J9 ]4.5.11 Final comments 106
  g7 q7 I" N0 a7 ?# }& dBibliographic notes 108
; \5 a8 f3 O( x$ q- p( m9 ?# J# M1 S5 How to use risk analysis to support decision-making 111
5.1 What is a good decision? 112
5.1.1 Features of a decision-making model 113
5.1.2 Decision-support tools 114
5.1.3 Discussion 119
3 P, L$ n. E$ O" L2 U7 \CONTENTS vii
1 m% z/ ~0 m) P- P" D, A6 }5.2 Some examples 122
5.2.1 Accident risk 122
+ D0 [* P; \6 L7 H  p5 M5.2.2 Scrap in place or complete removal of plant 125
* N" Y( x3 v2 U/ M. W5.2.3 Production system 130
5.2.4 Reliability target 131
5.2.5 Health risk 133
7 I7 J+ X- a3 V% T! J! Y9 F4 j& A5.2.6 Warranties 135
4 _! q, L/ Q0 \* \* D5 o7 z+ _5.2.7 Offshore development project 136
  |+ {& t1 ~" Z9 \: v9 T5.2.8 Risk assessment: National sector 138
5.2.9 Multi-attribute utility example 140
& Z' B7 a% K+ _) n5.3 Risk problem classification schemes 143
4 w- b, o4 k4 D/ |$ M: A5.3.1 A scheme based on consequences and uncertainties 143
1 F% U+ z6 I4 ?. c8 T. n5 Z- K5.3.2 A scheme based on closeness to hazard and level of authority 147
$ O& s! x& f1 F, v: o  {8 BBibliographic notes 158
6 Summary and conclusions 161
Appendix A: Basic theory of probability and statistics 165
A.1 Probability theory 165
' Z# A3 l6 r5 A  ?A.1.1 Types of probabilities 165
A.1.2 Probability rules 168
A.1.3 Random quantities (random variables) 172
A.1.4 Some common discrete probability distributions (models) 176
A.1.5 Some common continuous distributions (models) 178
) ^  I$ e4 T# t& F% ]! y; sA.1.6 Some remarks on probability models and their parameters 182
, G4 y0 M' [! k  E- [& E) ~, kA.1.7 Random processes 183
A.2 Classical statistical inference 184
A.2.1 Nonparametric estimation 184
A.2.2 Estimation of distribution parameters 185
A.2.3 Testing hypotheses 187
$ h2 S+ ?4 a1 o1 M0 L% s3 DA.2.4 Regression 188
A.3 Bayesian inference 189
A.3.1 Statistical (Bayesian) decision analysis 191
Bibliographic notes 192
Appendix B: Terminology 193
' Y9 X: x$ S, a: pB.1 Risk management: Relationships between key terms 195
% g5 T1 W: a3 G0 i# O5 a5 [* r# P  QReferences 197
Index 207

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