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Lecture

Variance Reduction: Strategies and Applications

In course

MATH-414: Stochastic simulation

The student who follows this course will get acquainted with computational tools used to analyze systems with uncertainty arising in engineering, physics, chemistry, and economics. Focus will be on sampling methods as Monte Carlo, quasi Monte Carlo, Mark ...

Description

This lecture covers the concept of variance reduction in stochastic simulation, discussing techniques such as stratification and conditional sampling. The instructor explains how to choose optimal allocation strategies and presents algorithms for generating replicas to estimate variance. The lecture emphasizes the importance of alternative choices in proportional allocation methods and provides examples to illustrate the concepts.

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Instructor

Fabio Nobile

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