3 papers
stat.ME2026
The Bayesian Gaussian Process Latent Variable Model for Spatio-Temporal Stream Networks
Marno Basson, Tobias M. Louw, Theresa R. Smith
A variational inference-based framework for training a multi-output Gaussian process latent variable model, specifically tailored to the tails-up spatio-temporal stream network, is…
stat.ME2023
Smoothing for age-period-cohort models: a comparison between splines and random process
Connor Gascoigne, Theresa Smith, Andrea Riebler
Age-Period-Cohort (APC) models are well used in the context of modelling health and demographic data to produce smooth estimates of each time trend. When smoothing in the context o…
stat.AP2023
Estimating Subnational Under-Five Mortality Rates Using a Spatio-Temporal Age-Period-Cohort Model
Connor Gascoigne, Theresa Smith, John Paige +1
Producing subnational estimates of the under-five mortality rate (U5MR) is a vital goal for the United Nations to reduce inequalities in mortality and well-being across the globe.…