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| 材料类型： | 互联网资源 |
|---|---|
| 文件类型： | 书, 互联网资源 |
| 所有的著者/提供者： |
Sheldon M Ross |
| ISBN: | 0125980639 9780125980630 |
| OCLC号码： | 69672100 |
| 描述： | xiii, 298 p. : ill. ; 24 cm. |
| 内容： | 2 Elements of Probability 5 -- 2.1 Sample Space and Events 5 -- 2.2 Axioms of Probability 6 -- 2.3 Conditional Probability and Independence 7 -- 2.4 Random Variables 9 -- 2.5 Expectation 11 -- 2.6 Variance 14 -- 2.7 Chebyshev's Inequality and the Laws of Large Numbers 16 -- 2.8 Some Discrete Random Variables 18 -- Binomial Random Variables 18 -- Poisson Random Variables 20 -- Geometric Random Variables 22 -- The Negative Binomial Random Variable 23 -- Hypergeometric Random Variables 24 -- 2.9 Continuous Random Variables 24 -- Uniformly Distributed Random Variables 25 -- Normal Random Variables 26 -- Exponential Random Variables 27 -- The Poisson Process and Gamma Random Variables 29 -- The Nonhomogeneous Poisson Process 32 -- 2.10 Conditional Expectation and Conditional Variance 33 -- The Conditional Variance Formula 34 -- 3 Random Numbers 41 -- 3.1 Pseudorandom Number Generation 41 -- 3.2 Using Random Numbers to Evaluate Integrals 42 -- 4 Generating Discrete Random Variables 49 -- 4.1 The Inverse Transform Method 49 -- 4.2 Generating a Poisson Random Variable 55 -- 4.3 Generating Binomial Random Variables 57 -- 4.4 The Acceptance-Rejection Technique 58 -- 4.5 The Composition Approach 60 -- 4.6 Generating Random Vectors 61 -- 5 Generating Continuous Random Variables 67 -- 5.1 The Inverse Transform Algorithm 67 -- 5.2 The Rejection Method 71 -- 5.3 The Polar Method for Generating Normal Random Variables 78 -- 5.4 Generating a Poisson Process 82 -- 5.5 Generating a Nonhomogeneous Poisson Process 83 -- 6 The Discrete Event Simulation Approach 93 -- 6.1 Simulation via Discrete Events 93 -- 6.2 A Single-Server Queueing System 94 -- 6.3 A Queueing System with Two Servers in Series 97 -- 6.4 A Queueing System with Two Parallel Servers 99 -- 6.5 An Inventory Model 102 -- 6.6 An Insurance Risk Model 103 -- 6.7 A Repair Problem 105 -- 6.8 Exercising a Stock Option 108 -- 6.9 Verification of the Simulation Model 110 -- 7 Statistical Analysis of Simulated Data 117 -- 7.1 The Sample Mean and Sample Variance 117 -- 7.2 Interval Estimates of a Population Mean 123 -- 7.3 The Bootstrapping Technique for Estimating Mean Square Errors 126 -- 8 Variance Reduction Techniques 137 -- 8.1 The Use of Antithetic Variables 139 -- 8.2 The Use of Control Variates 147 -- 8.3 Variance Reduction by Conditioning 154 -- Estimating the Expected Number of Renewals by Time t 164 -- 8.4 Stratified Sampling 166 -- 8.5 Applications of Stratified Sampling 175 -- Analyzing Systems Having Poisson Arrivals 176 -- Computing Multidimensional Integrals of Monotone Functions 180 -- Compound Random Vectors 182 -- 8.6 Importance Sampling 184 -- 8.7 Using Common Random Numbers 197 -- 8.8 Evaluating an Exotic Option 198 -- 8.9 Estimating Functions of Random Permutations and Random Subsets 203 -- Random Permutations 203 -- Random Subsets 206 -- 8.10 Appendix: Verification of Antithetic Variable Approach When Estimating the Expected Value of Monotone Functions 207 -- 9 Statistical Validation Techniques 219 -- 9.1 Goodness of Fit Tests 219 -- The Chi-Square Goodness of Fit Test for Discrete Data 220 -- The Kolmogorov-Smirnov Test for Continuous Data 222 -- 9.2 Goodness of Fit Tests When Some Parameters Are Unspecified 227 -- The Discrete Data Case 227 -- The Continuous Data Case 230 -- 9.3 The Two-Sample Problem 230 -- 9.4 Validating the Assumption of a Nonhomogeneous Poisson Process 237 -- 10 Markov Chain Monte Carlo Methods 245 -- 10.1 Markov Chains 245 -- 10.2 The Hastings-Metropolis Algorithm 248 -- 10.3 The Gibbs Sampler 251 -- 10.4 Simulated Annealing 262 -- 10.5 The Sampling Importance Resampling Algorithm 264 -- 11 Some Additional Topics 273 -- 11.1 The Alias Method for Generating Discrete Random Variables 273 -- 11.2 Simulating a Two-Dimensional Poisson Process 277 -- 11.3 Simulation Applications of an Identity for Sums of Bernoulli Random Variables 280 -- 11.4 Estimating the Distribution and the Mean of the First Passage Time of a Markov Chain 285 -- 11.5 Coupling from the Past 289. |
| 责任： | Sheldon M. Ross. |
| 更多信息： |
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...It is outstanding because it is what it is and no other textbook out there does this job. - Kris Ostaszewski, Illinois State University Examples are infinitely more interesting than in almost any other book! Ross always explains clearly, I especially enjoy the exposition of the brand new sections - Matt Carlton, Cal Polytechnic Institute 再读一些...
