156 citations · 391 across the 43 of their papers we have counts for
5 papers · 1 filter
Importance sampling squared for Bayesian inference in latent variable models
Minh-Ngoc Tran, Marcel Scharth, Michael K. Pitt +1
We consider Bayesian inference by importance sampling when the likelihood is analytically intractable but can be unbiasedly estimated. We refer to this procedure as importance samp…
Efficient variational inference for generalized linear mixed models with large datasets
David J Nott, Minh-Ngoc Tran, Anthony Y. C. Kuk +1
The article develops a hybrid Variational Bayes algorithm that combines the mean-field and fixed-form Variational Bayes methods. The new estimation algorithm can be used to approxi…
On the existence of moments for high dimensional importance sampling
Michael K. Pitt, Minh-Ngoc Tran, Marcel Scharth +1
Theoretical results for importance sampling rely on the existence of certain moments of the importance weights, which are the ratios between the proposal and target densities. In p…
Copula-type Estimators for Flexible Multivariate Density Modeling using Mixtures
Minh-Ngoc Tran, Paolo Giordani, Xiuyan Mun +2
Copulas are popular as models for multivariate dependence because they allow the marginal densities and the joint dependence to be modeled separately. However, they usually require…
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Minh-Ngoc Tran, Michael K. Pitt, Robert Kohn
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible…