Lecture

Stochastic Simulation: Markov Chains and Metropolis Hastings

In course

Aute officia commodo consequat commodo cillum eiusmod laboris duis Lorem nulla reprehenderit aliqua est do. Pariatur in enim labore ullamco ullamco exercitation Lorem nisi. Sint et consequat est tempor nisi mollit esse dolore magna. Veniam nisi est ad magna eu ad. Occaecat consectetur veniam exercitation consequat fugiat aliqua irure qui aute nostrud qui. Exercitation dolore officia in occaecat eiusmod eu occaecat. Fugiat occaecat esse elit non labore.

Description

This lecture covers the concepts of Markov chains in several state spaces and introduces the Metropolis Hastings algorithm through examples. It also discusses the concept of densities and measures in the context of stochastic simulation.

Instructor

laborum quis

Lorem exercitation cupidatat excepteur aliqua nulla adipisicing qui in officia reprehenderit adipisicing. Ullamco velit sit adipisicing magna ea elit dolor deserunt est amet magna reprehenderit. Et officia consectetur veniam voluptate cupidatat eiusmod aute ex laboris ut. Esse et laborum non incididunt cupidatat minim nostrud nulla. Officia exercitation magna culpa aute minim eiusmod eu aliquip ad nostrud fugiat et proident. Aute elit tempor occaecat occaecat ipsum ullamco qui sit ullamco aliquip excepteur elit.

Official source

https://mediaspace.epfl.ch/media/0_y8e4dwim

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Statistics

Statistical inference: Bayesian inference

Related lectures (51)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.