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Stochastic Simulation [Pehme köide]

(University of Oxford)
  • Formaat: Paperback / softback, 264 pages, kõrgus x laius x paksus: 242x160x13 mm, kaal: 375 g
  • Sari: Wiley Series in Probability and Statistics
  • Ilmumisaeg: 04-Apr-2006
  • Kirjastus: Wiley-Interscience
  • ISBN-10: 0470009608
  • ISBN-13: 9780470009604
Teised raamatud teemal:
  • Formaat: Paperback / softback, 264 pages, kõrgus x laius x paksus: 242x160x13 mm, kaal: 375 g
  • Sari: Wiley Series in Probability and Statistics
  • Ilmumisaeg: 04-Apr-2006
  • Kirjastus: Wiley-Interscience
  • ISBN-10: 0470009608
  • ISBN-13: 9780470009604
Teised raamatud teemal:
WILEY-INTERSCIENCE PAPERBACK SERIES

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

". . .this is a very competently written and useful addition to the statistical literature; a book every statistician should look at and that many should study!"
-Short Book Reviews, International Statistical Institute

". . .reading this book was an enjoyable learning experience. The suggestions and recommendations on the methods [ make] this book an excellent reference for anyone interested in simulation. With its compact structure and good coverage of material, it [ is] an excellent textbook for a simulation course."
-Technometrics

". . .this work is an excellent comprehensive guide to simulation methods, written by a very competent author. It is especially recommended for those users of simulation methods who want more than a 'cook book'. "
-Mathematics Abstracts

This book is a comprehensive guide to simulation methods with explicit recommendations of methods and algorithms. It covers both the technical aspects of the subject, such as the generation of random numbers, non-uniform random variates and stochastic processes, and the use of simulation. Supported by the relevant mathematical theory, the text contains a great deal of unpublished research material, including coverage of the analysis of shift-register generators, sensitivity analysis of normal variate generators, analysis of simulation output, and more.
Aims of Simulation
1(13)
The Tools
2(1)
Models
2(2)
Simulation as Experimentation
4(1)
Simulation in Inference
4(1)
Examples
5(7)
Literature
12(1)
Convention
12(2)
Exercises
13(1)
Pseudo-Random Numbers
14(39)
History and Philosophy
14(6)
Congruential Generators
20(6)
Shift-Register Generators
26(7)
Lattice Structure
33(9)
Shuffling and Testing
42(3)
Conclusions
45(1)
Proofs
46(7)
Exercises
50(3)
Random Variables
53(43)
Simple Examples
54(5)
General Principles
59(12)
Discrete Distributions
71(10)
Continuous Distributions
81(10)
Recommendations
91(5)
Exercises
92(4)
Stochastic Models
96(22)
Order Statistics
96(2)
Multivariate Distributions
98(2)
Poisson Processes and Lifetimes
100(4)
Markov Processes
104(1)
Gaussian Processes
105(5)
Point Processes
110(3)
Metropolis' Method and Random Fields
113(5)
Exercises
116(2)
Variance Reduction
118(24)
Monte-Carlo Integration
119(3)
Importance Sampling
122(1)
Control and Antithetic Variates
123(11)
Conditioning
134(3)
Experimental Design
137(5)
Exercises
139(3)
Output Analysis
142(28)
The Initial Transient
146(4)
Batching
150(5)
Time-Series Methods
155(2)
Regenerative Simulation
157(4)
A Case Study
161(9)
Exercises
169(1)
Uses of Simulation
170(30)
Statistical Inference
171(7)
Stochastic Methods in Optimization
178(8)
Systems of Linear Equations
186(3)
Quasi-Monte-Carlo Integration
189(4)
Sharpening Buffon's Needle
193(7)
Exercises
198(2)
References
200(15)
Appendix A. Computer Systems
215(2)
Appendix B. Computer Programs
217(18)
B.1 Form a x b mod c
217(2)
B.2 Check Primitive Roots
219(1)
B.3 Lattice Constants for Congruential Generators
220(7)
B.4 Test GFSR Generators
227(1)
B.5 Normal Variates
228(2)
B.6 Exponential Variates
230(1)
B.7 Gamma Variates
230(1)
B.8 Discrete Distributions
231(4)
Index 235


BRIAN D. RIPLEY, PhD, is Professor of Applied Statistics at University of Oxford. He is a Fellow of the Institute of Mathematical Statistics and the Royal Society of Edinburgh and is also a member of the International Statistical Institute. He is the author of Spatial Statistics, which was published by Wiley in 1981.