4 papers
Bayesian outcome selection modelling
Khue-Dung Dang, Louise M. Ryan, Richard J. Cook +3
Psychiatric and social epidemiology often involves assessing the effects of environmental exposure on outcomes that are difficult to measure directly. To address this problem, it i…
Bayesian structural equation modeling for data from multiple cohorts
Khue-Dung Dang, Louise M. Ryan, Tugba Akkaya-Hocagil +7
While it is well known that high levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, the exact nature of the dose response is less well…
Subsampling MCMC - An introduction for the survey statistician
Matias Quiroz, Mattias Villani, Robert Kohn +2
The rapid development of computing power and efficient Markov Chain Monte Carlo (MCMC) simulation algorithms have revolutionized Bayesian statistics, making it a highly practical i…
Subsampling Sequential Monte Carlo for Static Bayesian Models
David Gunawan, Khue-Dung Dang, Matias Quiroz +2
We show how to speed up Sequential Monte Carlo (SMC) for Bayesian inference in large data problems by data subsampling. SMC sequentially updates a cloud of particles through a sequ…