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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…
stat.ME2024
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.ME2024
Contrastive linear regression
Boyang Zhang, Sarah Nyquist, Andrew Jones +2
Contrastive dimension reduction methods have been developed for case-control study data to identify variation that is enriched in the foreground (case) data X relative to the backg…