Concurrent object regression

DOI10.1214/22-EJS2040zbMath1493.62644arXiv2101.05026MaRDI QIDQ2161189

Satarupa Bhattacharjee, Hans-Georg Müller

Publication date: 4 August 2022

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2101.05026

zbMATH Keywords

fMRIlocal regressionvarying coefficient modelrandom objectsFréchet regressionconcurrent regressiongeneral metric spacemetric-space valued data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) General nonlinear regression (62J02) Statistics on metric spaces (62R20)

Related Items

Fréchet single index models for object response regression, Single index Fréchet regression

Uses Software

• fda (R)

Cites Work

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• Fréchet regression for random objects with Euclidean predictors
• Peter Hall, functional data analysis and random objects
• Inference for functional data with applications
• Statistical methods with varying coefficient models
• Fréchet means for distributions of persistence diagrams
• Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging
• Large sample theory of intrinsic and extrinsic sample means on manifolds. I
• Statistical estimation in varying coefficient models
• Geometry of the space of phylogenetic trees
• Ridge regression for the functional concurrent model
• Varying coefficient model for modeling diffusion tensors along white matter tracts
• Barycentric subspace analysis on manifolds
• Functional concurrent linear regression model for spatial images
• Functional data analysis.
• Large sample theory of intrinsic and extrinsic sample means on manifolds. II.
• A Riemannian framework for tensor computing
• Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis
• Distances and inference for covariance operators
• Inferring stochastic dynamics from functional data
• Overview of object oriented data analysis
• Riemannian $L^{p}$ center of mass: Existence, uniqueness, and convexity
• Varying coefficient models for sparse noise-contaminated longitudinal data
• Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data
• Smoothing Spline Estimation for Varying Coefficient Models With Repeatedly Measured Dependent Variables
• Varying-coefficient models and basis function approximations for the analysis of repeated measurements
• Smoothing Spline Estimation in Varying-Coefficient Models
• A Geometric study of Wasserstein spaces: Euclidean spaces
• Nonparametric Regression for Spherical Data
• Generalized Gaussian Process Regression Model for Non-Gaussian Functional Data
• Strong laws of large numbers for generalizations of Fréchet mean sets
• Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics
• Riemannian Geometry of Symmetric Positive Definite Matrices via Cholesky Decomposition
• A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain
• Intrinsic Regression Models for Positive-Definite Matrices With Applications to Diffusion Tensor Imaging
• Functional Varying Coefficient Models for Longitudinal Data
• A Differential Geometric Approach to the Geometric Mean of Symmetric Positive-Definite Matrices
• Regression Models on Riemannian Symmetric Spaces
• Variable Selection in Nonparametric Varying-Coefficient Models for Analysis of Repeated Measurements
• Gaussian Process Functional Regression Modeling for Batch Data
• Geometric Means in a Novel Vector Space Structure on Symmetric Positive‐Definite Matrices
• Functional Data Analysis for Sparse Longitudinal Data
• Functional data analysis for density functions by transformation to a Hilbert space