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Lecture
Metropolis-Hastings Algorithm: Implementation and Case Study
Description
This lecture covers the Metropolis-Hastings algorithm, explaining how to choose a Markov process, initialize the chain, simulate the next state, and work in the log-space. It also presents a case study on Swissmetro transportation mode choice model with variables, data collection, and Python code implementation.
Official source
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