| Detailed information |
| Original study plan |
Bachelor's programme Technical Mathematics 2023W |
| Objectives |
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.
|
| Subject |
Pseudo-random number generators, simulation of random numbers from specific distributions, simulation of stochastic processes, simulation of stochastic differential equations, Monte Carlo integration.
|
| Criteria for evaluation |
Programming project in R and project presentation.
|
| Methods |
Blackboard presentation, supported by lecture slides and software R
|
| Language |
English and French |
| Study material |
- 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
|
| Changing subject? |
No |
| Earlier variants |
They also cover the requirements of the curriculum (from - to)
201WTMSSTSV20: VO Stochastic simulation (2020W-2022S)
TMCPAVOSIMU: VO Stochastic simulation (2004S-2020S)
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