activity
20132023
most citedStructured Functional Principal Component Analysis

2 citations · 5 across the 6 of their papers we have counts for

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Showing stat.MEShow all

8 papers · 1 filter

stat.ME20231 cited

Regression in quotient metric spaces with a focus on elastic curves

Lisa Steyer, Almond Stöcker, Sonja Greven

We propose regression models for curve-valued responses in two or more dimensions, where only the image but not the parametrization of the curves is of interest. Examples of such d…

stat.ME2022

Classification ensembles for multivariate functional data with application to mouse movements in web surveys

Amanda Fernández-Fontelo, Felix Henninger, Pascal J. Kieslich +2

We propose new ensemble models for multivariate functional data classification as combinations of semi-metric-based weak learners. Our models extend current semi-metric-type method…

stat.ME2021

Multivariate Functional Additive Mixed Models

Alexander Volkmann, Almond Stöcker, Fabian Scheipl +1

Multivariate functional data can be intrinsically multivariate like movement trajectories in 2D or complementary like precipitation, temperature, and wind speeds over time at a giv…

stat.ME2020

Selective Inference for Additive and Linear Mixed Models

David Rügamer, Philipp F. M. Baumann, Sonja Greven

This work addresses the problem of conducting valid inference for additive and linear mixed models after model selection. One possible solution to overcome overconfident inference…

stat.ME2018

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…

stat.ME2018

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,…