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stat.CO2026
Neural Inference Functions for Margins for Time Series Copula Models
Daniel Fynn, David Gunawan, Andrew Zammit-Mangion
Copula models are widely employed in multivariate time series analysis because they permit flexible modelling of marginal distributions independently of the dependence structure, w…
stat.CO2025
Recursive variational Gaussian approximation with the Whittle likelihood for linear non-Gaussian state space models
Bao Anh Vu, David Gunawan, Andrew Zammit-Mangion
Parameter inference for linear and non-Gaussian state space models is challenging because the likelihood function contains an intractable integral over the latent state variables.…
stat.CO2024
R-VGAL: A Sequential Variational Bayes Algorithm for Generalised Linear Mixed Models
Bao Anh Vu, David Gunawan, Andrew Zammit-Mangion
Models with random effects, such as generalised linear mixed models (GLMMs), are often used for analysing clustered data. Parameter inference with these models is difficult because…