Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1154475 | Statistics & Probability Letters | 2015 | 7 Pages |
Abstract
We prove explicit error bounds for Markov chain Monte Carlo (MCMC) methods to compute expectations of functions with unbounded stationary variance. We assume that there is a p∈(1,2)p∈(1,2) so that the functions have finite LpLp-norm. For uniformly ergodic Markov chains we obtain error bounds with the optimal order of convergence n1/p−1n1/p−1 and if there exists a spectral gap we almost get the optimal order. Further, a burn-in period is taken into account and a recipe for choosing the burn-in is provided.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Daniel Rudolf, Nikolaus Schweizer,