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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 2025-3-23 11:39:46 | 只看該作者
Principles for Intelligent Decision Aidingthe entries of the parameter vector are some fixed values. For instance, the traditional . signal is a particular case (with one level) of multilevel sparse sequences. We apply an empirical Bayesian approach, namely we put an appropriate prior modeling the multilevel sparsity and make data-dependent
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發(fā)表于 2025-3-24 09:58:16 | 只看該作者
Tareq Ahram,Redha Taiar,Kamiar Aminianvariate normal distribution is a common choice for the random error term in an SUR model, the multivariate .-distribution is also popular for robustness considerations. However, the multivariate .-distribution is elliptical which leads to the limitation that the degrees of freedom of its marginal di
17#
發(fā)表于 2025-3-24 12:40:48 | 只看該作者
Chao Yin Wu,Hsiao Rong Huang,Mao Jiun Wangloping practical algorithms is the computation of the likelihood. We address this problem through the use of a fast method to track the probability density function of the stochastic differential equation. The method applies quadrature to the Chapman–Kolmogorov equation associated with a temporal di
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發(fā)表于 2025-3-24 17:30:01 | 只看該作者
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