Lecture

Stochastic Simulation: Metropolis-Hastings Algorithm

In course

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Description

This lecture covers the Metropolis-Hastings algorithm, MALA, and convergence diagnostics in stochastic simulation. It explains the goal of sampling from a target density and the process of generating proposal values. The instructor discusses the importance of choosing the proposal density and the concepts of convergence diagnostics. The lecture also delves into the application of the algorithm in various scenarios and the evaluation of acceptance-rejection criteria.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_1swcfem4

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Ontological neighbourhood

Statistics

Data collection: Statistical sampling

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