Perfectly random sampling of truncated multinormal distributions

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dc.creatorFernandez, Pedro J.
dc.creatorFerrari, Pablo A.
dc.creatorGrynberg, Sebastian
dc.date2005-05-25
dc.date2007-09-25
dc.date.accessioned2026-07-07T08:31:55Z
dc.date.available2026-07-07T08:31:55Z
dc.descriptionThe target measure $μ$ is the distribution of a random vector in a box $\cB$, a Cartesian product of bounded intervals. The Gibbs sampler is a Markov chain with invariant measure $μ$. A ``coupling from the past'' construction of the Gibbs sampler is used to show ergodicity of the dynamics and to perfectly simulate $μ$. An algorithm to sample vectors with multinormal distribution truncated to $\cB$ is then implemented.
dc.description22 pages, submitted to Journal of Applied Probability
dc.identifierhttps://arxiv.org/abs/math/0505522
dc.identifierhttp://arxiv.org/abs/math/0505522
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/138643
dc.subjectProbability
dc.subjectStatistics Theory
dc.subject60G15, 60G10, 65C05
dc.titlePerfectly random sampling of truncated multinormal distributions
dc.typetext

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