Using the Metropolis-Hastings algorithm in Bayesian data analysis procedures
Petro Ivanovich Bidyuk, Volodymyr Beglytsia, Aleksandr Gozhyj, Irina Kalinina · 2019 IEEE 14th International Conference on Computer Sciences and Information Technologies (CSIT) · 2019
The paper studies the features of the Metropolis-Hastings algorithm and its applications in Bayesian data analysis problems. The application of the Monte-Carlo Markov chains (MCMC) methods for the generation of complex posterior density of high dimensionality is substantiated. An example of the application of the Metropolis-Hastings algorithm has been considered.