12 citations · 13 across the 3 of their papers we have counts for
5 papers
Principal component analysis in Bayes spaces for sparsely sampled density functions
Lisa Steyer, Sonja Greven
This paper presents a novel approach to functional principal component analysis (FPCA) in Bayes spaces in the setting where densities are the object of analysis, but only few indiv…
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…
Elastic Full Procrustes Analysis of Plane Curves via Hermitian Covariance Smoothing
Almond Stöcker, Manuel Pfeuffer, Lisa Steyer +1
Determining the mean shape of a collection of curves is not a trivial task, in particular when curves are only irregularly/sparsely sampled at discrete points. We newly propose an…
Functional additive models on manifolds of planar shapes and forms
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 tran…
Elastic analysis of irregularly or sparsely sampled curves
Lisa Steyer, Almond Stöcker, Sonja Greven
We provide statistical analysis methods for samples of curves when the image but not the parametrisation of the curves is of interest. A parametrisation invariant analysis can be b…