3 papers
stat.ME2026
Approximate Likelihood-Based Inference for Spatial Generalized Linear Mixed Models
Samuel I. Watson, Yixin Wang, Emanuele Giorgi
We study maximum likelihood estimation for spatial generalized linear mixed models with Gaussian process approximations using a stochastic Newton-Raphson algorithm. We consider two…
stat.ME2026
A flexible class of latent variable models for the analysis of antibody response data
Emanuele Giorgi, Jonas Wallin
Existing approaches to modelling antibody concentration data are mostly based on finite mixture models that rely on the assumption that individuals can be divided into two distinct…
stat.ME2025
A Time-Series Model for Areal Data Using Area-Specific Gaussian Processes with Spatially Correlated Hyperparameters
Alejandro Rozo Posada, Oswaldo Gressani, Christel Faes +4
In many applied settings, areal data are observed repeatedly over long time periods, as commonly occurs in infectious disease surveillance and environmental or demographic monitori…