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title:
Explicit error bounds for reversible Markov chain Monte Carlo
name:
Rudolf
first name:
Daniel
location/conference:
SPP-JT09
PRESENTATION-link:
http://dfg-spp1324.de/download/jt09/talks/rudolf.pdf
abstract:
Markov chain Monte Carlo methods for approximating the expectation
play a crucial role in numerous applications. The problem is to compute the expectation with respect to some distribution. A straight generation of the desired distribution is in general not possible. Thus it is reasonable to use Markov chain sampling with a burn-in. An explicit error bound with respect to different norms of the function will be presented. By the estimation the well known asymptotical limit of the error is attained, i.e. there is no gap between the estimate and the asymptotical behavior.