Functional Additive Models on Manifolds of Planar Shapes and Forms

DOI10.1080/10618600.2023.2175687arXiv2109.02624OpenAlexW3215436041MaRDI QIDQ6141186

Unnamed Author, Sonja Greven, Almond Stöcker

Publication date: 22 January 2024

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2109.02624

zbMATH Keywords

visualizationshape analysisboostingfunctional regressiontensor-product model

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Fréchet regression for random objects with Euclidean predictors
• Functional and shape data analysis
• Multivariate varying coefficient model for functional responses
• Intrinsic statistics on Riemannian manifolds: Basic tools for geometric measurements
• A Bayesian regression model for multivariate functional data
• Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study
• Boosting flexible functional regression models with a high number of functional historical effects
• Additive regression for non-Euclidean responses and predictors
• Locally polynomial Hilbertian additive regression
• Additive regression with Hilbertian responses
• Geodesic regression and the theory of least squares on Riemannian manifolds
• Functional data analysis.
• Intrinsic polynomials for regression on Riemannian manifolds
• A unified framework of constrained regression
• Bayesian function-on-function regression for multilevel functional data
• Statistical Shape Analysis, with Applications in R
• Wavelet-based Functional Mixed Models
• On the asymptotics of penalized splines
• Variable Selection and Model Choice in Geoadditive Regression Models
• Riemannian center of mass and mollifier smoothing
• Boosting With theL₂Loss
• Modeling Motor Learning Using Heteroscedastic Functional Principal Components Analysis
• Fitting Smooth Paths to Speherical Data
• Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
• The functional linear array model
• Boosting functional response models for location, scale and shape with an application to bacterial competition
• A general framework for functional regression modelling
• Intrinsic Regression Models for Positive-Definite Matrices With Applications to Diffusion Tensor Imaging
• Regression Models on Riemannian Symmetric Spaces
• Functional Additive Models
• Shape-space smoothing splines for planar landmark data
• Functional Data Analysis for Sparse Longitudinal Data
• Riemannian geometry.
• Kriging prediction for manifold-valued random fields

This page was built for publication: Functional Additive Models on Manifolds of Planar Shapes and Forms