In this chapter, we present a general introduction to Monte Carlo (MC)-based methods, sampling methodologies, stratification methods, and variance reduction techniques. In the first part, we will discuss the theoretical basis and the convergence proprieties of MC methods. The next part is devoted to pseudorandom and quasi-random number generation, the generation of random variables and the application of stratification. It is followed by techniques for correlation and discrepancy control. The third part presents the concept of Latin Hypercube Sampling (LHS). The last part introduces the concept of Multi-Level Monte Carlo (MLMC).

Back to Top

Document information

Published on 01/01/2019

DOI: 10.1007/978-3-319-77767-2_16
Licence: CC BY-NC-SA license

Document Score


Views 15
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?