2 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
A General Framework for Multivariate Functional Principal Component Analysis of Amplitude and Phase Variation
Clara Happ, Fabian Scheipl, Alice-Agnes Gabriel +1
Functional data typically contains amplitude and phase variation. In many data situations, phase variation is treated as a nuisance effect and is removed during preprocessing, alth…
Boosting Functional Response Models for Location, Scale and Shape with an Application to Bacterial Competition
Almond Stöcker, Sarah Brockhaus, Sophia Schaffer +3
We extend Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to regression with functional response. This allows us to simultaneously model point-wise mean curves,…
Inference for -Boosting
David Rügamer, Sonja Greven
We propose a statistical inference framework for the component-wise functional gradient descent algorithm (CFGD) under normality assumption for model errors, also known as -Bo…
Conditional Model Selection in Mixed-Effects Models with cAIC4
Benjamin Säfken, David Rügamer, Thomas Kneib +1
Model selection in mixed models based on the conditional distribution is appropriate for many practical applications and has been a focus of recent statistical research. In this pa…