Functional generalized linear models provide a flexible framework for relating a scalar response to functional and scalar predictors, but their conventional formulation requires specification of the response distribution and is typically developed for a single population. We propose a semiparametric functional generali...
Structural magnetic resonance imaging (MRI) is informative for studying progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD), but incorporating high-dimensional images into survival models requires methods that accommodate irregular brain domains and yield interpretable spatial effects. We propo...
Jia-Hui Feng, Muye Nanshan, Hao-Lun Shi et al.· Statistical Methods in Medic...· 0 citations
We study continuous-time relational event data, where time-stamped dyadic interactions reflect both individual node propensities and evolving relational proximity. We propose a dynamic latent space model for inhomogeneous Poisson processes, where event intensities depend on node-specific activity parameters and time-va...
In function-on-function regression, the coefficient surface $\beta(s,t)$ may exhibit complex support structure---from localized patches to global patterns such as disconnected regions, bands, or rings---where effect similarity does not align with Euclidean proximity. Projection-based methods that rely on fixed basis ex...
