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Explicit error bounds for Markov chain Monte Carlo

- Daniel Rudolf
- Mathematics
- 16 August 2011

Wir beweisen explizite, d.h., nicht-asymptotische Fehlerabschatzungen fur Markov-Ketten-Monte-Carlo-Methoden. Ziel ist es, den Erwartungswert einer Funktion f bzgl. eines Mases π zu berechnen.… Expand

Perturbation theory for Markov chains via Wasserstein distance

- Daniel Rudolf, Nikolaus Schweizer
- Mathematics
- 13 March 2015

Perturbation theory for Markov chains addresses the question how small differences in the transitions of Markov chains are reflected in differences between their distributions. We prove powerful and… Expand

On the size of the largest empty box amidst a point set

- C. Aistleitner, A. Hinrichs, Daniel Rudolf
- Mathematics, Computer Science
- Discret. Appl. Math.
- 8 July 2015

TLDR

Positivity of hit-and-run and related algorithms

- Daniel Rudolf, Mario Ullrich
- Mathematics
- 18 December 2012

We prove positivity of the Markov operators that correspond to the hit-and-run algorithm, random scan Gibbs sampler, slice sampler and Metropolis algorithm with positive proposal. In particular, the… Expand

Explicit error bounds for lazy reversible Markov chain Monte Carlo

- Daniel Rudolf
- Mathematics, Computer Science
- J. Complex.
- 23 May 2008

TLDR

Error bounds for computing the expectation by Markov chain Monte Carlo

- Daniel Rudolf
- Computer Science, Mathematics
- Monte Carlo Methods Appl.
- 12 June 2009

TLDR

On a Generalization of the Preconditioned Crank–Nicolson Metropolis Algorithm

- Daniel Rudolf, Björn Sprungk
- Mathematics, Computer Science
- Found. Comput. Math.
- 14 April 2015

TLDR

An Upper Bound of the Minimal Dispersion via Delta Covers

- Daniel Rudolf
- Mathematics, Computer Science
- ArXiv
- 5 January 2017

TLDR

Discrepancy bounds for uniformly ergodic Markov chain quasi-Monte Carlo

- J. Dick, Daniel Rudolf, Houying Zhu
- Mathematics
- 11 March 2013

Markov chains can be used to generate samples whose distribution approximates a given target distribution. The quality of the samples of such Markov chains can be measured by the discrepancy between… Expand

Computation of Expectations by Markov Chain Monte Carlo Methods

- E. Novak, Daniel Rudolf
- Mathematics
- 8 November 2013

Markov chain Monte Carlo (MCMC) methods are a very versatile and widely used tool to compute integrals and expectations. In this short survey we focus on error bounds, rules for choosing the burn in,… Expand

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