370 citations · 556 across the 23 of their papers we have counts for
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Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
C. Happ, S. Greven
Existing approaches for multivariate functional principal component analysis are restricted to data on the same one-dimensional interval. The presented approach focuses on multivar…
Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data
Jona Cederbaum, Marianne Pouplier, Phil Hoole +1
We propose an estimation approach to analyse correlated functional data which are observed on unequal grids or even sparsely. The model we use is a functional linear mixed model, a…
Generalized Functional Additive Mixed Models
Fabian Scheipl, Jan Gertheiss, Sonja Greven
We propose a comprehensive framework for additive regression models for non-Gaussian functional responses, allowing for multiple (partially) nested or crossed functional random eff…
Identifiability in penalized function-on-function regression models
Fabian Scheipl, Sonja Greven
Regression models with functional responses and covariates constitute a powerful and increasingly important model class. However, regression with functional data poses well known a…
Longitudinal high-dimensional principal components analysis with application to diffusion tensor imaging of multiple sclerosis
Vadim Zipunnikov, Sonja Greven, Haochang Shou +3
We develop a flexible framework for modeling high-dimensional imaging data observed longitudinally. The approach decomposes the observed variability of repeatedly measured high-dim…