978 resultados para Hastings (Mich.)
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Signatur des Originals: S 36/F10485
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Signatur des Originals: S 36/G00158
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Signatur des Originals: S 36/G02660
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Signatur des Originals: S 36/G12614
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Signatur des Originals: S 36/G03534
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Signatur des Originals: S 36/G03535
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G. Salzberger
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Fil: Rubino, Atilio Raúl. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET); Argentina.
Resumo:
Fil: Rubino, Atilio Raúl. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET); Argentina.
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Sign.: A12
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Markov Chain Monte Carlo methods are widely used in signal processing and communications for statistical inference and stochastic optimization. In this work, we introduce an efficient adaptive Metropolis-Hastings algorithm to draw samples from generic multimodal and multidimensional target distributions. The proposal density is a mixture of Gaussian densities with all parameters (weights, mean vectors and covariance matrices) updated using all the previously generated samples applying simple recursive rules. Numerical results for the one and two-dimensional cases are provided.