Foundations and methods of stochastic simulation. A first course The present book consists of 276 pages organised in 9 Chapters. It is a graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material), and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems, and prepares the reader to use simulation in research as well as practice. The book is a rigorous but concise treatment, emphasizing lasting principles, but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research. The VBASim simulation package is used and shows examples. In my opinion, it is an avegare level book and recommended for MSc, PhD students.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Hong, L. Jeff; Luo, Jun; Nelson, Barry L.: Chance constrained selection of the best (2015)
- Ji, Xinyang; Fan, Shunhou; Fan, Wei: Parameter estimation for a class of lifetime models (2014)
- Nelson, Barry L.: Foundations and methods of stochastic simulation. A first course (2013)