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Communication Dans Un Congrès Année : 2012

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

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Nicolas Desassis

Résumé

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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Dates et versions

hal-00709250 , version 1 (18-06-2012)

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  • HAL Id : hal-00709250 , version 1

Citer

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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