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020 _a9783030861940
024 7 _a10.1007/978-3-030-86194-0
_2doi
040 _aES-VaU
_bspa
_cES-VaU
_dES-VaU
050 4 _aT57.6-.97
_b2021 EB
100 1 _aNelson, Barry L.
_eautor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 0 0 _aFoundations and Methods of Stochastic Simulation :
_bA First Course
_cby Barry L Nelson, Linda Pei
250 _a2nd ed. 2021.
264 1 _aCham
_c2021
_bSpringer International Publishing
300 _a1 recurso en línea
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 0 _aInternational Series in Operations Research & Management Science
_x2214-7934
_v316
505 0 _aChapter 1: Why Do We Simulate -- Chapter 2: Simulation Programming: Quick Start -- Chapter 3: Examples -- Chapter 4: Simulation Programming with PythonSim -- Chapter 5: Three Views of Simulation -- Chapter 6: Simulation Input -- Chapter 7: Simulation Output -- Chapter 8: Experiment Design and Analysis -- Chapter 9: Simulation Optimization and Sensitivity -- Chapter 10: Simulation for Research -- References -- Index.
520 _aThis graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works. The book is rigorous and complete, but concise and accessible, providing all necessary background material. Object-oriented programming of simulations is illustrated in Python, while the majority of the book is programming language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers to use simulation in their research. A solutions manual for end-of-chapter exercises is available for instructors.
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-86194-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942 _2lcc
_cLE
988 _aSpringer_Business_2021
999 _c239090
_d239090