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Daniel Rudolf
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Zitiert von
Zitiert von
Jahr
Perturbation theory for Markov chains via Wasserstein distance
D Rudolf, N Schweizer
Bernoulli 24 (4A), 2610-2639, 2018
1362018
Explicit error bounds for Markov chain Monte Carlo
D Rudolf
Dissertationes Mathematicae 485 (2012), 1-93, 2011
1222011
On a generalization of the preconditioned Crank–Nicolson Metropolis algorithm
D Rudolf, B Sprungk
Foundations of Computational Mathematics 18 (2), 309-343, 2018
902018
Error bounds for computing the expectation by Markov chain Monte Carlo
D Rudolf
Monte Carlo Methods and Applications 16 (3-4), 323-342, 2010
522010
Explicit error bounds for lazy reversible Markov chain Monte Carlo
D Rudolf
Journal of Complexity 25 (1), 11-24, 2009
442009
On the size of the largest empty box amidst a point set
C Aistleitner, A Hinrichs, D Rudolf
Discrete applied mathematics 230, 146-150, 2017
412017
Positivity of hit-and-run and related algorithms
D Rudolf, M Ullrich
Electronic Communications in Probability 18, 2013
372013
Perturbation bounds for Monte Carlo within Metropolis via restricted approximations
F Medina-Aguayo, D Rudolf, N Schweizer
Stochastic Processes and their Applications 130 (4), 2200-2227, 2020
342020
An upper bound of the minimal dispersion via delta covers. Contemporary Computational Mathematics-a Celebration of the 80th Birthday of Ian Sloan
D Rudolf
arXiv preprint arXiv:1701.06430, 1099-1108, 2018
30*2018
A strong law of large numbers for scrambled net integration
AB Owen, D Rudolf
arXiv preprint arXiv:2002.07859, 2020
272020
Tractability of the approximation of high-dimensional rank one tensors
E Novak, D Rudolf
Constructive Approximation 43 (1), 1-13, 2016
242016
Convergence of hybrid slice sampling via spectral gap
K Łatuszyński, D Rudolf
Advances in Applied Probability 56 (4), 1440-1466, 2024
23*2024
Comparison of hit-and-run, slice sampler and random walk metropolis
D Rudolf, M Ullrich
Journal of Applied Probability 55 (4), 1186-1202, 2018
192018
Quantitative spectral gap estimate and Wasserstein contraction of simple slice sampling
V Natarovskii, D Rudolf, B Sprungk
The Annals of Applied Probability 31 (2), 806-825, 2021
172021
On a Metropolis–Hastings importance sampling estimator
D Rudolf, B Sprungk
Electronic Journal of Statistics 14 (1), 857-889, 2020
172020
Optimal confidence for Monte Carlo integration of smooth functions
RJ Kunsch, D Rudolf
Advances in Computational Mathematics 45 (5), 3095-3122, 2019
172019
Solvable integration problems and optimal sample size selection
RJ Kunsch, E Novak, D Rudolf
Journal of Complexity 53, 40-67, 2019
162019
Discrepancy bounds for uniformly ergodic Markov chain quasi-Monte Carlo
J Dick, D Rudolf, H Zhu
Annals of Applied Probability 26 (5), 3178-3205, 2016
152016
Hit-and-run for numerical integration
D Rudolf
Monte Carlo and Quasi-Monte Carlo Methods 2012, 597-612, 2013
152013
Error bounds of MCMC for functions with unbounded stationary variance
D Rudolf, N Schweizer
Statistics & Probability Letters 99, 6-12, 2015
142015
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