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Titlebook: Bayesian Statistics in Action; BAYSM 2016, Florence Raffaele Argiento,Ettore Lanzarone,Alessandra Matt Conference proceedings 2017 Springer

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發(fā)表于 2025-3-28 15:03:13 | 只看該作者
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發(fā)表于 2025-3-28 21:33:47 | 只看該作者
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發(fā)表于 2025-3-29 02:25:35 | 只看該作者
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發(fā)表于 2025-3-29 06:16:14 | 只看該作者
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發(fā)表于 2025-3-29 11:09:55 | 只看該作者
Conference proceedings 2017 to connect with the Bayesian community at large, to exchange ideas, and to network with others working in the same field. The contributions develop and apply Bayesian methods in a variety of fields, ranging from the traditional (e.g., biostatistics and reliability) to the most innovative ones (e.g., big data and networks)..
46#
發(fā)表于 2025-3-29 13:06:04 | 只看該作者
https://doi.org/10.1007/978-3-030-74009-2otype and virus biotype were considered as baseline covariates and error terms were assumed to follow a modified standard Gumbel distribution. Frequentist approach to these models was also considered in order to compare the results of the study from both statistical methodologies.
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發(fā)表于 2025-3-29 19:31:56 | 只看該作者
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發(fā)表于 2025-3-29 21:59:28 | 只看該作者
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發(fā)表于 2025-3-30 01:54:07 | 只看該作者
Human Interaction with Complex Systems. In this paper, we propose to suppress these issues by extending the Bayesian update by a sort of likelihood tempering, moderating the impact of observed data to inference. The method is compared to the generic dynamic model averaging and to an alternative solution via sequential quasi-Bayesian mixture modeling.
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發(fā)表于 2025-3-30 06:04:41 | 只看該作者
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