We study the numerical computation of an expectation of a bounded function f with respect to a measure given by a non-normalized density on a convex body K ⊂ Rd. We assume that the density is log-concave, satisfies a variability condition and is not too narrow. In [19, 25, 26] it is required that K is the Euclidean unit ball. We consider general convex bodies or even the whole Rd and show that the integration problem satisfies a refined form of tractability. The main tools are the hit-and-run algorithm and an error bound of a multi run Markov chain Monte Carlo method. © Springer-Verlag Berlin Heidelberg 2013.
CITATION STYLE
Rudolf, D. (2013). Hit-and-Run for Numerical Integration. In Springer Proceedings in Mathematics and Statistics (Vol. 65, pp. 597–612). https://doi.org/10.1007/978-3-642-41095-6_31
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