no code implementations • 26 May 2022 • Amanda Fernández-Fontelo, Felix Henninger, Pascal J. Kieslich, Frauke Kreuter, Sonja Greven
We propose new ensemble models for multivariate functional data classification as combinations of semi-metric-based weak learners.
no code implementations • 6 Sep 2021 • Almond Stöcker, Lisa Steyer, Sonja Greven
The "shape" of a planar curve and/or landmark configuration is considered its equivalence class under translation, rotation and scaling, its "form" its equivalence class under translation and rotation while scale is preserved.
1 code implementation • 11 Mar 2021 • Alexander Volkmann, Almond Stöcker, Fabian Scheipl, Sonja Greven
Multivariate functional data can be intrinsically multivariate like movement trajectories in 2D or complementary like precipitation, temperature, and wind speeds over time at a given weather station.
Methodology
no code implementations • 5 Nov 2020 • Amanda Fernández-Fontelo, Pascal J. Kieslich, Felix Henninger, Frauke Kreuter, Sonja Greven
We use data from a survey on respondents' employment history and demographic information, in which we experimentally manipulate the difficulty of several questions.
1 code implementation • 4 May 2018 • 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 $L_2$-Boosting.
1 code implementation • 30 May 2017 • Sarah Brockhaus, David Rügamer, Sonja Greven
In addition to mean regression, quantile regression models as well as generalized additive models for location scale and shape can be fitted with FDboost.
Computation
1 code implementation • 20 Sep 2016 • David Rügamer, Sarah Brockhaus, Kornelia Gentsch, Klaus Scherer, Sonja Greven
The link between different psychophysiological measures during emotion episodes is not well understood.