Sampling from Linear Multivariate Densities View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2009

AUTHORS

Wolfgang Hörmann , Josef Leydold

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.

PAGES

143-151

Book

TITLE

Advancing the Frontiers of Simulation

ISBN

978-1-4419-0816-2
978-1-4419-0817-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/b110059_7

DOI

http://dx.doi.org/10.1007/b110059_7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008709519


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