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Risk analysis : a quantitative guide 2nd ed

Risk analysis : a quantitative guide 2nd ed (Loan 6 times)

Material type
단행본
Personal Author
Vose, David. Vose, David.
Title Statement
Risk analysis : a quantitative guide / David Vose.
판사항
2nd ed.
Publication, Distribution, etc
Chichester ;   New York :   Wiley,   c2000.  
Physical Medium
x, 418 p. : ill. ; 26 cm.
ISBN
047199765X (alk. paper)
General Note
Rev. ed. of: Quantitative risk analysis, c1996.  
Bibliography, Etc. Note
Includes bibliographical references (p. [411]) and index.
Subject Added Entry-Topical Term
Monte Carlo method. Risk assessment -- Mathematical models. Monte-Carlo, Methode de. Evaluation du risque -- Modeles mathematiques.
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001 000045137326
005 20041209135301
008 041209s2000 enka b 001 0 eng
010 ▼a 99052968
015 ▼a GBA2-26962
020 ▼a 047199765X (alk. paper)
040 ▼a DLC ▼c DLC ▼d FPU ▼d UKM ▼d OCLCQ ▼d 211009
050 0 0 ▼a QA298 ▼b .V67 2000
082 0 0 ▼a 658.4/0352 ▼2 21
090 ▼a 658.40352 ▼b V962r2
100 1 ▼a Vose, David.
245 1 0 ▼a Risk analysis : ▼b a quantitative guide / ▼c David Vose.
250 ▼a 2nd ed.
260 ▼a Chichester ; ▼a New York : ▼b Wiley, ▼c c2000.
300 ▼a x, 418 p. : ▼b ill. ; ▼c 26 cm.
500 ▼a Rev. ed. of: Quantitative risk analysis, c1996.
504 ▼a Includes bibliographical references (p. [411]) and index.
650 0 ▼a Monte Carlo method.
650 0 ▼a Risk assessment ▼x Mathematical models.
650 7 ▼a Monte-Carlo, Methode de. ▼2 ram
650 7 ▼a Evaluation du risque ▼x Modeles mathematiques. ▼2 ram
700 1 ▼a Vose, David. ▼t Quantitative risk analysis.

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 658.40352 V962r2 Accession No. 121101201 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents


CONTENTS
Preface = ⅸ
Preface to First Edition = xi
1 Introduction = 1
 1.1 Structure of this book = 2
 1.2 The risk assessment process = 6
2 Quantitative Risk Analysis, Uncertainty and Variability = 13
 2.1 Method of moments = 14
 2.2 Exact algebraic solutions = 15
 2.3 Monte Carlo simulation = 16
 2.4 Uncertainty and variability = 18
3 Probability Theory and Statistics = 29
 3.1 Probability distribution equations = 29
 3.2 Statistical measures = 31
 3.3 Probability rules and Venn diagrams = 36
 3.4 Probability theorems = 41
 3.5 Least squares linear regression = 48
 3.6 Rank order correlation coefficient = 53
 3.7 Reliability theory = 55
4 How Monte Carlo Simulation Works = 57
 4.1 Random sampling from input distributions = 57
 4.2 Random number generator seeds = 64
 4.3 Rank order correlation = 64
5 Stochastic Processes = 67
 5.1 Introduction = 67
 5.2 The binomial process = 67
 5.3 The Poisson process = 73
 5.4 The hypergeometric process = 79
 5.5 Renewal processes = 84
 5.6 Mixture distributions = 86
 5.7 Miscellaneous examples = 87
6 Probability Distributions = 99
 6.1 Discrete and continuous distributions = 99
 6.2 Bounded and unbounded distributions = 101
 6.3 Parametric and non-parametric distributions = 102
 6.4 Probability distribution functions = 103
 6.5 Approximation of one distribution with another = 131
 6.6 Recursive formulae for discrete distributions = 140
 6.7 A visual observation on the behaviour of distributions = 143
7 Quantifying Uncertainty About Model Parameters = 145
 7.1 Classical statistics = 146
 7.2 Bayesian inference = 149
 7.3 The Bootstrap = 181
 7.4 Maximum entropy principle = 191
 7.5 Which technique should you use? = 192
 7.6 Examples to compare traditional statistical inference, Bayesian inference and the Bootstrap = 193
 7.7 Adding uncertainty in simple linear least squares regression analysis = 193
8 Building a Risk Analysis Model = 201
 8.1 Is it possible to model the problem? = 201
 8.2 Types of risk analysis model = 202
 8.3 Designing a spreadsheet model = 203
 8.4 Separating uncertainty and variability in a risk analysis model = 203
 8.5 Splitting up a low-probability model = 209
 8.6 Including rare events in a model = 212
 8.7 Setting out a model clearly = 214
 8.8 Model uncertainty = 214
 8.9 Risk analysis software = 215
9 Determining Distributions of Variability from Data = 217
 9.1 Analysing the properties of the observed data = 218
 9.2 Fitting a non-parametric distribution to the observed data = 223
 9.3 Fitting a first-order parametric distribution to observed data = 235
 9.4 Fitting a second-order parametric distribution to observed data = 252
10 Defining Distributions from Expert Opinion = 263
 10.1 Introduction = 263
 10.2 Sources of error in subjective estimation = 264
 10.3 Modelling techniques = 271
 10.4 Conducting a brainstorming session = 283
 10.5 Conducting the interview = 284
11 Modelling Dependencies = 291
 11.1 Introduction = 291
 11.2 Rank order correlation = 294
 11.3 Correlation matrices = 300
 11.4 The envelope method = 303
 11.5 Multiple correlation using a look-up table = 311
12 Time Series Projections = 313
 12.1 Comparison of forecasting techniques = 313
 12.2 Na$$\ddot i$$ve forecasts = 314
 12.3 Short-term forecasting = 317
 12.4 Medium-term forecasting = 322
 12.5 Long-term forecasting = 327
 12.6 A variable-rate Poisson process = 329
13 Project Risk Analysis = 335
 13.1 Cost risk analysis = 336
 13.2 Schedule risk analysis = 340
 13.3 Project risk analysis software = 347
14 Animal Import and Food Safety Risk Assessment = 349
 14.1 Testing for an infected animal = 351
 14.2 Estimating true prevalence in a population = 357
 14.3 Importing problems = 358
 14.4 Confidence of detecting an infected group = 361
 14.5 Miscellaneous animal health and food safety problems = 364
15 Presenting and Interpreting Risk Analysis Results = 373
 15.1 Writing a risk analysis report = 373
 15.2 Explaining a model's assumptions = 374
 15.3 Graphical presentation of a model's results = 379
 15.4 Statistical methods of analysing results = 392
 15.5 Using discounted cashflow calculations in risk analysis = 403
References = 407
Bibliography = 411
Index = 413


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