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Lecture

Markov Chain Monte Carlo

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 Markov Chain Monte Carlo method, focusing on the Metropolis-Hastings algorithm. It explains how to generate samples from a target probability distribution using this algorithm, constructing a transition kernel. The lecture also discusses the detailed balance condition and the importance of density functions in the process.

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Instructor

Fabio Nobile

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