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A guide to simulation

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  • "Changes and additions are sprinkled throughout. Among the significant new features are: - Markov-chain simulation (Sections 1. 3, 2. 6, 3. 6, 4. 3, 5. 4. 5, and 5. 5)' - gradient estimation (Sections 1. 6, 2. 5, and 4. 9)' - better handling of asynchronous observations (Sections 3. 3 and 3. 6)' - radically updated treatment of indirect estimation (Section 3. 3)' - new section on standardized time series (Section 3. 8)' - better way to generate random integers (Section 6. 7. 1) and fractions (Appendix L, program UNIFL)' - thirty-seven new problems plus improvements of old problems. Helpful comments by Peter Glynn, Barry Nelson, Lee Schruben, and Pierre Trudeau stimulated several changes. Our new random integer routine extends ideas of Aarni Perko. Our new random fraction routine implements Pierre L'Ecuyer's recommended composite generator and provides seeds to produce disjoint streams. We thank Springer-Verlag and its late editor, Walter Kaufmann-Bilhler, for inviting us to update the book for its second edition. Working with them has been a pleasure. Denise St-Michel again contributed invaluable text-editing assistance. Preface to the First Edition Simulation means driving a model of a system with suitable inputs and observing the corresponding outputs. It is widely applied in engineering, in business, and in the physical and social sciences."
  • "Simulation means driving a model of a system with suitable inputs and observing the corresponding outputs. It is widely applied in engineering, in business, and in the physical and social sciences. Simulation method ology araws on computer. science, statistics, and operations research and is now sufficiently developed and coherent to be called a discipline in its own right. A course in simulation is an essential part of any operations re search or computer science program. A large fraction of applied work in these fields involves simulation; the techniques of simulation, as tools, are as fundamental as those of linear programming or compiler construction, for example. Simulation sometimes appears deceptively easy, but perusal of this book will reveal unexpected depths. Many simulation studies are statistically defective and many simulation programs are inefficient. We hope that our book will help to remedy this situation. It is intended to teach how to simulate effectively. A simulation project has three crucial components, each of which must always be tackled: (1) data gathering, model building, and validation; (2) statistical design and estimation; (3) programming and implementation. Generation of random numbers (Chapters 5 and 6) pervades simulation, but unlike the three components above, random number generators need not be constructed from scratch for each project. Usually random number packages are available. That is one reason why the chapters on random numbers, which contain mainly reference material, follow the ch!lPters deal ing with experimental design and output analysis."
  • "Variance reduction. Output analysis. Rational choice of input distributions. Nonuniform random numbers. Uniform random numbers. Simulation programming. Programming to reduce the variance."
  • "Uporaba diskretnih simulacij na področju računalniškega programiranja."

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  • "Matériel didactique"
  • "Electronic books"
  • "Digitale Computersimulation"

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  • "A Guide to Simulation"
  • "A Guide to simulation"
  • "A guide to simulation"
  • "A guide to simulation"@en
  • "Guide to simulation"

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