Sampling from Linear Multivariate Densities

Wolfgang Hörmann () and Josef Leydold ()
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Wolfgang Hörmann: Boğaziçi University
Josef Leydold: WU Wien

A chapter in Advancing the Frontiers of Simulation, 2009, pp 143-151 from Springer

Abstract: Abstract It is well known that the generation of random vectors with non-independent components is difficult. Nevertheless, we propose a new and very simple generation algorithm for multivariate linear densities over point-symmetric domains. Among other applications it can be used to design a simple decomposition-rejection algorithm for multivariate concave distributions.

Keywords: Random Vector; Importance Sampling; Linear Density; Multivariate Distribution; Symmetric Domain (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4419-0817-9_7

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DOI: 10.1007/b110059_7

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