Monte-Carlo Methods

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Keywords

Monte-Carlo Methods

Objectives

Monte Carlo methods is a set of techniques based on simulated random variables and whose aim is to solve numerically a deterministic problem.

Developed knowledges: to know how to use an appropriate Monte Carlo methods to some a numerical problem.m

Number of hours

  • Travaux Dirigés : 19.5h
  • Cours Magistral : 19.5h

Form of assessment

First session

Second session

Continuous assessment: 100%

Final examination: 0%

Remedial examination: 100 %

Remedial examination length: 2 hours

Syllabus

 1. Simulation of random variables: inversion method, acceptance-rejection method, etc.

2. Numerical integration: introduction, general principle, variance reduction techniques.

3. Stochastic optimization: recall and complements on Markov chains, Monte Carlo Markov chain (random walk on a graph, Metropolis-Hasting algorithm, Gibbs measure, simulated annealing), genetic algorith

In brief

ECTS credits 4.0

Number of hours 39.0

Level of study Master degree level

Contact(s)

Organizational unit

Administrative contact(s)

Secrétariat de Mathématiques

Email : secretariat-mathematiques @ univ-pau.fr

Places

  • Pau