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math.ST2019
Markov Chain Monte Carlo on Finite State Spaces
Tobias Siems
We elaborate the idea behind Markov chain Monte Carlo (MCMC) methods in a mathematically coherent, yet simple and understandable way. To this end, we proof a pivotal convergence th…
math.ST2018
A note on the Metropolis-Hastings acceptance probabilities for mixture spaces
Tobias Siems, Lisa Koeppel
This work is driven by the ubiquitous dissent over the abilities and contributions of the Metropolis-Hastings and reversible jump algorithm within the context of trans dimensional…