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 pseudorandom 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 
Pseudorandom 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. SchÃ¤ffler

Changing subject? 
No 
Earlier variants 
They also cover the requirements of the curriculum (from  to) 201WTMSSTSV20: VO Stochastic simulation (2020W2022S) TMCPAVOSIMU: VO Stochastic simulation (2004S2020S)
