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20182024
most citedBeing Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics

18 citations · 26 across the 12 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

stat.AP2022★ 18 cited

Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics

Joshua J. Bon, Adam Bretherton, Katie Buchhorn +12

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 sta…

stat.ME2022★ 1 cited

clusterBMA: Bayesian model averaging for clustering

Owen Forbes, Edgar Santos-Fernandez, Paul Pao-Yen Wu +7

Various methods have been developed to combine inference across multiple sets of results for unsupervised clustering, within the ensemble clustering literature. The approach of rep…

stat.ME2022★ 2 cited

Bayesian Design with Sampling Windows for Complex Spatial Processes

Katie Buchhorn, Kerrie Mengersen, Edgar Santos-Fernandez +2

Optimal design facilitates intelligent data collection. In this paper, we introduce a fully Bayesian design approach for spatial processes with complex covariance structures, like…

stat.AP2022★ 2 cited

On the intrinsic dimensionality of Covid-19 data: a global perspective

Abhishek Varghese, Edgar Santos-Fernandez, Francesco Denti +2

This paper aims to develop a global perspective of the complexity of the relationship between the standardised per-capita growth rate of Covid-19 cases, deaths, and the OxCGRT Covi…

stat.CO2022★ 1 cited

SSNbayes: An R package for Bayesian spatio-temporal modelling on stream networks

Edgar Santos-Fernandez, Jay M. Ver Hoef, James M. McGree +3

Spatio-temporal models are widely used in many research areas from ecology to epidemiology. However, most covariance functions describe spatial relationships based on Euclidean dis…