4 citations · 10 across the 6 of their papers we have counts for
6 papers
Error bounds for simultaneous Wasserstein contractive adaptive increasingly rare MCMC
Julian Hofstadler, Daniel Rudolf
We investigate adaptive increasingly rare Markov chain Monte Carlo algorithms and the associated time-average estimator for approximating expectations. Under a simultaneous Wassers…
Solving Poisson's equation for Wasserstein contractive Markov chains
Julian Hofstadler
We study Poisson's equation in the context of general state space Markov chains. For chains satisfying a contraction assumption w.r.t. a Wasserstein distance, we show that a soluti…
Optimal convergence rates of MCMC integration for functions with unbounded second moment
Julian Hofstadler
We study the Markov chain Monte Carlo (MCMC) estimator for numerical integration for functions that do not need to be square integrable w.r.t. the invariant distribution. For chain…
Almost sure convergence rates of adaptive increasingly rare Markov chain Monte Carlo
Julian Hofstadler, Krzysztof Latuszynski, Gareth O. Roberts +1
We consider adaptive increasingly rare Markov chain Monte Carlo (MCMC) algorithms, which are adaptive MCMC methods, where the adaptation concerning the "past'' happens less and les…
The Spherical Cap Discrepancy of HEALPix Points
Damir Ferizović, Julian Hofstadler, Michelle Mastrianni
In this paper we show that the spherical cap discrepancy of the point set given by centers of pixels in the HEALPix tessellation (short for Hierarchical, Equal Area and iso-Latitud…
Consistency of randomized integration methods
Julian Hofstadler, Daniel Rudolf
We prove that a class of randomized integration methods, including averages based on -sequences, Latin hypercube sampling, Frolov points as well as Cranley-Patterson rotatio…