[ 201WTMSSTSV22 ] VL Stochastic Simulation

Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B3 - Bachelor's programme 3. year Mathematics Evelyn Buckwar 2 hpw Johannes Kepler University Linz
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)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment