Source Themes

Latent Transport Models for Multivariate Functional Data

Multivariate functional data present theoretical and practical complications which are not found in univariate functional data. One of these is a situation where the component functions of multivariate functional data are positive and are subject to …

Learning delay dynamics for multivariate stochastic processes, with application to the prediction of the growth rate of COVID-19 cases in the United States

Delay differential equations form the underpinning of many complex dynamical systems. The forward problem of solving random differential equations with delay has received increasing attention in recent years. Motivated by the challenge to predict the …

Comparison of Diagnostic Predictors of Neonatal Survivability in Non-domestic Caprinae

Various biological testing methods have been utilized to identify passive transfer of immunoglobulins in neonates of non-domestic Caprinae species, but their diagnostic value is poorly understood. This retrospective study evaluated whether five …

Cross-Component Registration for Multivariate Functional Data, with Application to Growth Curves

Multivariate functional data are becoming ubiquitous with the advance of modern technology. Multivariate functional data are substantially more complex than univariate functional data. In particular, we study a novel model for multivariate functional …

Time Dynamics of COVID-19

We apply tools from functional data analysis to model cumulative trajectories of COVID-19 cases across countries, establishing a framework for quantifying and comparing cases and deaths across countries longitudinally. It emerges that a country’s …

Mountaineers on Mount Everest, effects of age, sex, prior experience, and crowding on rates of success and death

Mount Everest is an extreme environment for humans. Nevertheless, hundreds of mountaineers attempt to summit Everest each year. In a previous study, we analyzed how probabilities of summiting and of dying on Everest related to a climber’s sex, age, …

A practical method to quantify knowledge‐based DVH prediction accuracy and uncertainty with reference cohorts

The adoption of knowledge-based dose-volume histogram (DVH) prediction models for assessing organ-at-risk (OAR) sparing in radiotherapy necessitates quantification of prediction accuracy and uncertainty. Moreover, DVH prediction error bands should be …