| Detailinformationen |
| Quellcurriculum |
Bachelorstudium Technische Mathematik 2023W |
| Ziele |
(*)At the end of the course, students will have an overview of the main techniques for the simulation of pseudo-random numbers from diverse distributions, know how to use these numbers to simulate different stochastic processes, and gained an insight into Monte Carlo methods. Moreover, students will have worked with the software R.
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| Lehrinhalte |
(*)Pseudo-random number generators, simulation of random numbers from specific distributions, simulation of stochastic processes, simulation of stochastic differential equations, Monte Carlo integration.
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| Beurteilungskriterien |
(*)Programming project in R and project presentation.
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| Lehrmethoden |
(*)Blackboard presentation, supported by lecture slides and software R
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| Abhaltungssprache |
English |
| Literatur |
(*)- Random Number Generation and Monte Carlo Methods, J. E. Gentle
- Simulation, S. Ross,
- Simulation and Inference for Stochastic Differential Equations With R Examples, S. M. Iacus
- Stochastik: Theorie und Anwendungen, D. Meintrup and S. Schäffler
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| Lehrinhalte wechselnd? |
Nein |
| Frühere Varianten |
Decken ebenfalls die Anforderungen des Curriculums ab (von - bis)
201WTMSSTSV20: VO Stochastische Simulation (2020W-2022S)
TMCPAVOSIMU: VO Stochastische Simulation (2004S-2020S)
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