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stat.ME2026

Bayesian Spatiotemporal Wombling

Aritra Halder, Didong Li, Sudipto Banerjee

Stochastic process models for spatiotemporal data underlying random fields find substantial utility in a range of scientific disciplines. Subsequent to predictive inference on the…

stat.ME2026

Hierarchical Probabilistic Principal Component Analysis of Longitudinal Data

Xinyu Zhang, Ameer Qaqish, D. Y. Lin +1

In many longitudinal studies, a large number of variables are measured repeatedly over time, with substantial missing data. Existing methods, such as probabilistic principal compon…