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08/21/2023
The Multivariate Bernoulli detector: Change point estimation in discrete survival analysis
Time-to-event data are often recorded on a discrete scale with multiple,...
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05/10/2022
Bayesian clustering of multiple zero-inflated outcomes
Several applications involving counts present a large proportion of zero...
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05/09/2022
On a wider class of prior distributions for graphical models
Gaussian graphical models are useful tools for conditional independence ...
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03/22/2022
Bayesian Learning of Graph Substructures
Graphical models provide a powerful methodology for learning the conditi...
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08/03/2021
The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models
Gaussian graphical models can capture complex dependency structures amon...
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03/09/2021
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
Markov chain Monte Carlo (MCMC) is a powerful methodology for the approx...
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05/14/2020
Bayesian Joint Modelling of Recurrence and Survival: a Conditional Approach
Recurrent event processes describe the stochastic repetition of an event...
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09/15/2019