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A FIRST COURSE IN MONTE CARLO shows you how to design, perform, and analyze the results of MC experiments based on independent replications, Markov chain MC, and MC optimization. The text emphasizes the variance-reducing techniques of importance sampling, stratified sampling, Rao-Blackwellization, c...
Αποθηκεύτηκε σε:
| Κύριος συγγραφέας: | |
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| Γλώσσα: | Undetermined English |
| Έκδοση: |
Belmont, CA
Thomson Brooks/cole
2006
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| Θέματα: | |
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| Thư viện lưu trữ: | Trung tâm Học liệu Trường Đại học Trà Vinh |
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| Περίληψη: | A FIRST COURSE IN MONTE CARLO shows you how to design, perform, and analyze the results of MC experiments based on independent replications, Markov chain MC, and MC optimization. The text emphasizes the variance-reducing techniques of importance sampling, stratified sampling, Rao-Blackwellization, control variates, antithetic variates, and quasi-random numbers. For solving optimization problems it describes several MC techniques, including simulated annealing, simulated tempering, swapping, stochastic tunneling, and genetic algorithms. Examples from many areas show how these techniques perform in practice. Hands-on exercises allow you to experience challenges encountered when solving real problems. An answer key to selected problems is included |
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| Φυσική περιγραφή: | xi, 414 p. ill. 25 cm |
| ISBN: | 053442046X 9780534420468 |