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Journal Article

Computation of expectations by Markov chain Monte Carlo methods

Lecture Notes in Computational Science and Engineering (2014) 102 397-411
DOI: 10.1007/978-3-319-08159-5_20
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Abstract

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, high dimensional problems and tractability versus curse of dimension.

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APA

Novak, E., & Rudolf, D. (2014). Computation of expectations by Markov chain Monte Carlo methods. Lecture Notes in Computational Science and Engineering, 102, 397–411. https://doi.org/10.1007/978-3-319-08159-5_20

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