14 citations · 35 across the 35 of their papers we have counts for
5 papers · 1 filter
Neural posterior inference with state-space models for calibrating ice sheet simulators
Bao Anh Vu, Andrew Zammit-Mangion, David Gunawan +2
Ice sheet models are routinely used to quantify and project an ice sheet's contribution to sea level rise. In order for an ice sheet model to generate realistic projections, its pa…
Bayesian copula-based spatial random effects models for inference with complex spatial data
Alan Pearse, David Gunawan, Noel Cressie
In this article, we develop fully Bayesian, copula-based, spatial-statistical models for large, noisy, incomplete, and non-Gaussian spatial data. Our approach includes novel constr…
Bayesian Inference for Non-Gaussian Simultaneous Autoregressive Models with Missing Data
Anjana Wijayawardhana, David Gunawan, Thomas Suesse
Standard simultaneous autoregressive (SAR) models typically assume normally distributed errors, an assumption often violated in real-world datasets that frequently exhibit non-norm…
Enhancing Efficiency of Local Projections Estimation with Volatility Clustering in High-Frequency Data
Chew Lian Chua, David Gunawan, Sandy Suardi
This paper advances the local projections (LP) method by addressing its inefficiency in high-frequency economic and financial data with volatility clustering. We incorporate a gene…
Fast Variational Boosting for Latent Variable Models
David Gunawan, David Nott, Robert Kohn
We consider the problem of estimating complex statistical latent variable models using variational Bayes methods. These methods are used when exact posterior inference is either in…