1 citations · 1 across the 5 of their papers we have counts for
5 papers
Bayesian variable and hazard structure selection in the General Hazard model
Yulong Chen, Jim Griffin, Francisco Javier Rubio
The proportional hazards (PH) and accelerated failure time (AFT) models are the most widely used hazard structures for analysing time-to-event data. When the goal is to identify va…
Fast Bayesian inference in a class of sparse linear mixed effects models
M-Z. Spyropoulou, J. Hopker, J. E. Griffin
Linear mixed effects models are widely used in statistical modelling. We consider a mixed effects model with Bayesian variable selection in the random effects using spike-and-slab…
Modelling between- and within-season trajectories in elite athletic performance data
M. Spyropoulou, J. G. Hopker, J. E. Griffin
Athletic performance follows a typical pattern of improvement and decline during a career. This pattern is also often observed within-seasons, as an athlete aims for their performa…
Expressing and visualizing model uncertainty in Bayesian variable selection using Cartesian credible sets
J. E. Griffin
Modern regression applications can involve hundreds or thousands of variables which motivates the use of variable selection methods. Bayesian variable selection defines a posterior…
Structure Learning with Adaptive Random Neighborhood Informed MCMC
Alberto Caron, Xitong Liang, Samuel Livingstone +1
In this paper, we introduce a novel MCMC sampler, PARNI-DAG, for a fully-Bayesian approach to the problem of structure learning under observational data. Under the assumption of ca…