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stat.ME2026
Bayesian Nonparametric Detection of Anomalies in Multivariate Functional Data
Daniel Krasnov, David Stephens
Anomalies in functional data arise from rare or distinct processes that deviate from the dominant data-generating mechanism. Detecting such departures is essential in applications…
stat.ME2026
Posterior Uncertainty for Targeted Parameters in Bayesian Bootstrap Procedures
Magid Sabbagh, David A. Stephens
We propose a general method to carry out a valid Bayesian analysis of a finite-dimensional `targeted' parameter in the presence of a finite-dimensional nuisance parameter. We apply…
stat.ME2024
Computational Considerations for the Linear Model of Coregionalization
Renaud Alie, David A. Stephens, Alexandra M. Schmidt
In the last two decades, the linear model of coregionalization (LMC) has been widely used to model multivariate spatial processes. However, it can be a challenging task to conduct…