Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 46, No. 3 (September/septembre 2018), pp. 399-415 (17 pages) For sparse and high-dimensional data analysis, a valid ...

Bayesian approaches have emerged as powerful tools in forensic anthropology, particularly in the domain of age estimation. By integrating prior knowledge with new observational data, these methods ...

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 180, No. 4 (OCTOBER 2017), pp. 1191-1209 (19 pages) Area level models, such as the Fay–Herriot model, aim to improve ...

Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...