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Simulation of a Gaussian random vector: A propagative version of the Gibbs sampler.

Abstract : Starting from the Gibbs sampler, an iterative algorithm is designed for simulating a gaussian random vector, that requires neither the inversion nor the factorization of a covariance matrix, without resting on a markovian assumption. A brief survey is given of the various ways to implement it. An example illustrates its feasibility, and a theoretical result is stated about its rate of convergence.
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https://hal-mines-paristech.archives-ouvertes.fr/hal-00709250
Contributor : Nicolas Desassis <>
Submitted on : Monday, June 18, 2012 - 12:02:03 PM
Last modification on : Thursday, September 24, 2020 - 4:34:05 PM

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  • HAL Id : hal-00709250, version 1

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Christian Lantuéjoul, Nicolas Desassis. Simulation of a Gaussian random vector: A propagative version of the Gibbs sampler.. The 9th International Geostatistics Congress, Oslo., Jun 2012, Oslo, Norway. pp.1747181. ⟨hal-00709250⟩

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