Markov Chain Monte Carlo Methods

Thomas Neifer
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Thomas Neifer: Bonn-Rhein-Sieg University of Applied Sciences

A chapter in Operations Research and Management, 2024, pp 167-183 from Springer

Abstract: Abstract The Markov Chain Monte Carlo (MCMC) methods based on the Bayes theorem are used when an a posteriori distribution does not have a tractable form and is therefore not fully known or directly usable (e.g., for maximum a posteriori parameter estimation). MCMC methods overcome intractability by drawing parameter values from known distributions and correlating these drawings until they approximately match the target distribution. MCMC methods represent a powerful class of algorithms for processing data and knowledge, which is why they are also called a "quantum leap in statistics".

Date: 2024
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DOI: 10.1007/978-3-031-47206-0_9

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