Reuven Y. Rubinstein (1938-2012)

Description matérielle : XI-260 p.
Description : Note : Bibliogr. p. 255-258. Index
Édition : New York ; Chichester ; Brisbane [etc.] : J. Wiley & sons , cop. 1986

3rd ed.
Description matérielle : 1 online resource (435 pages)
Description technique : La pagination de l'édition imprimée correspondante est de : 435 pages
Description : Note : SIMULATION AND THE MONTE CARLO METHOD; CONTENTS; PREFACE; ACKNOWLEDGMENTS; CHAPTER 1 PRELIMINARIES; 1.1 INTRODUCTION; 1.2 RANDOM EXPERIMENTS; 1.3 CONDITIONAL PROBABILITY AND INDEPENDENCE; 1.4 RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS; 1.5 SOME IMPORTANT DISTRIBUTIONS; 1.6 EXPECTATION; 1.7 JOINT DISTRIBUTIONS; 1.8 FUNCTIONS OF RANDOM VARIABLES; 1.8.1 Linear Transformations; 1.8.2 General Transformations; 1.9 TRANSFORMS; 1.10 JOINTLY NORMAL RANDOM VARIABLES; 1.11 LIMIT THEOREMS; 1.12 POISSON PROCESSES; 1.13 MARKOV PROCESSES; 1.13.1 Markov Chains; 1.13.2 Classification of States
1.13.3 Limiting Behavior1.13.4 Reversibility; 1.13.5 Markov Jump Processes; 1.14 GAUSSIAN PROCESSES; 1.15 INFORMATION; 1.15.1 Shannon Entropy; 1.15.2 Kullback-Leibler Cross-Entropy; 1.15.3 Maximum Likelihood Estimator and Score Function; 1.15.4 Fisher Information; 1.16 CONVEX OPTIMIZATION AND DUALITY; 1.16.1 Lagrangian Method; 1.16.2 Duality; PROBLEMS; REFERENCES; CHAPTER 2 RANDOM NUMBER, RANDOM VARIABLE, AND STOCHASTIC PROCESS GENERATION; 2.1 INTRODUCTION; 2.2 RANDOM NUMBER GENERATION; 2.2.1 Multiple Recursive Generators; 2.2.2 Modulo 2 Linear Generators; 2.3 RANDOM VARIABLE GENERATION
2.3.1 Inverse-Transform Method2.3.2 Alias Method; 2.3.3 Composition Method; 2.3.4 Acceptance-Rejection Method; 2.4 GENERATING FROM COMMONLY USED DISTRIBUTIONS; 2.4.1 Generating Continuous Random Variables; 2.4.2 Generating Discrete Random Variables; 2.5 RANDOM VECTOR GENERATION; 2.5.1 Vector Acceptance-Rejection Method; 2.5.2 Generating Variables from a Multinormal Distribution; 2.5.3 Generating Uniform Random Vectors over a Simplex; 2.5.4 Generating Random Vectors Uniformly Distributed over a Unit Hyperball and Hypersphere
2.5.5 Generating Random Vectors Uniformly Distributed inside a Hyperellipsoid2.6 GENERATING POISSON PROCESSES; 2.7 GENERATING MARKOV CHAINS AND MARKOV JUMP PROCESSES; 2.7.1 Random Walk on a Graph; 2.7.2 Generating Markov Jump Processes; 2.8 GENERATING GAUSSIAN PROCESSES; 2.9 GENERATING DIFFUSION PROCESSES; 2.10 GENERATING RANDOM PERMUTATIONS; PROBLEMS; REFERENCES; CHAPTER 3 SIMULATION OF DISCRETE-EVENT SYSTEMS; 3.1 INTRODUCTION; 3.2 SIMULATION MODELS; 3.2.1 Classification of Simulation Models; 3.3 SIMULATION CLOCK AND EVENT LIST FOR DEDS; 3.4 DISCRETE-EVENT SIMULATION; 3.4.1 Tandem Queue
3.4.2 Repairman ProblemPROBLEMS; REFERENCES; CHAPTER 4 STATISTICAL ANALYSIS OF DISCRETE-EVENT SYSTEMS; 4.1 INTRODUCTION; 4.2 ESTIMATORS AND CONFIDENCE INTERVALS; 4.3 STATIC SIMULATION MODELS; 4.4 DYNAMIC SIMULATION MODELS; 4.4.1 Finite-Horizon Simulation; 4.4.2 Steady-State Simulation; 4.5 BOOTSTRAP METHOD; PROBLEMS; REFERENCES; CHAPTER 5 CONTROLLING THE VARIANCE; 5.1 INTRODUCTION; 5.2 COMMON AND ANTITHETIC RANDOM VARIABLES; 5.3 CONTROL VARIABLES; 5.4 CONDITIONAL MONTE CARLO; 5.4.1 Variance Reduction for Reliability Models; 5.5 STRATIFIED SAMPLING; 5.6 MULTILEVEL MONTE CARLO.. - 5.7 IMPORTANCE SAMPLING
La pagination de l'édition imprimée correspondante est de : 435 pages
Édition : Newark : Wiley , [2016]
Autre : Dirk P. Kroese