Descripción
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Adaptive Rejection Metropolis Sampling (ARMS) is a well-known MCMC scheme for generating samples from one-dimensional target distributions. ARMS is widely used within Gibbs sampling, where automatic and fast samplers are often needed to draw from univariate full-conditional densities. In this work, we propose an alternative adaptive algorithm (IA2RMS) that overcomes the main drawback of ARMS (an uncomplete adaptation of the proposal in some cases), speeding up the convergence of the chain to the target. Numerical results show that IA2RMS outperforms the standard ARMS, providing a correlation among samples close to zero. | |
Internacional
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Si |
Nombre congreso
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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Tipo de participación
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960 |
Lugar del congreso
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Florencia (Italia) |
Revisores
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Si |
ISBN o ISSN
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978-1-4799-2893-4 |
DOI
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10.1109/ICASSP.2014.6855158 |
Fecha inicio congreso
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04/05/2014 |
Fecha fin congreso
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09/05/2014 |
Desde la página
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8048 |
Hasta la página
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8052 |
Título de las actas
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Proceedings of the 39th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |