1 citations · 2 across the 3 of their papers we have counts for
4 papers
Bayesian Changepoint Analysis
Tobias Siems
In my PhD thesis, we elaborate upon Bayesian changepoint analysis, whereby our focus is on three big topics: approximate sampling via MCMC, exact inference and uncertainty quantifi…
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…
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…
Simultaneous Credible Regions for Multiple Changepoint Locations
Tobias Siems, Marc Hellmuth, Volkmar Liebscher
Within a Bayesian retrospective framework, we present a way of examining the distribution of \cps through a novel set estimator. For a given level, , we aim at smallest sets tha…