1 citations · 1 across the 2 of their papers we have counts for
2 papers
math.ST2025
On a conjecture of Roverato regarding G-Wishart normalising constants
Ching Wong, Giusi Moffa, Jack Kuipers
The evaluation of G-Wishart normalising constants is a core component for Bayesian analyses for Gaussian graphical models, but remains a computationally intensive task in general.…
stat.ME2024★ 1 cited
A new way to evaluate G-Wishart normalising constants via Fourier analysis
Ching Wong, Giusi Moffa, Jack Kuipers
The G-Wishart distribution is a core component for the Bayesian analysis of Gaussian graphical models as the conjugate prior for the precision matrix. Evaluating the marginal likel…