Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...
Brazilian Journal of Probability and Statistics, Vol. 33, No. 4, Contributions to the Special Volume of the XIV EBEB (“Encontro Brasileiro de Estatística Bayesiana”) (2019), pp. 782-800 (19 pages) ...
Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...
A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...
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