| Autor: |
Bon, Joshua J., Bretherton, Adam, Buchhorn, Katie, Cramb, Susanna, Drovandi, Christopher, Hassan, Conor, Jenner, Adrianne L., Mayfield, Helen J., McGree, James M., Mengersen, Kerrie, Price, Aiden, Salomone, Robert, Santos-Fernandez, Edgar, Vercelloni, Julie, Wang, Xiaoyu |
| Předmět: |
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| Zdroj: |
Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences; 5/15/2023, Vol. 381 Issue 2247, p1-29, 29p |
| Abstrakt: |
Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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