Modeling Time-Varying Random Objects and Dynamic Networks
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Publication:6110737
DOI10.1080/01621459.2021.1917416zbMath1515.62138arXiv2104.04628OpenAlexW3155422029MaRDI QIDQ6110737
Hans-Georg Müller, Paromita Dubey
Publication date: 6 July 2023
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2104.04628
metric spacefunctional data analysisempirical dynamicstime-varying networksFréchet mean trajectoryobject time coursestime-varying distributions
Computational methods for problems pertaining to statistics (62-08) Functional data analysis (62R10)
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Correction to “Modeling Time-Varying Random Objects and Dynamic Networks”, Two-sample and change-point inference for non-Euclidean valued time series
Cites Work
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- Fréchet regression for random objects with Euclidean predictors
- Toward a comprehensive framework for the spatiotemporal statistical analysis of longitudinal shape data
- Inference for functional data with applications
- Nonparametric clustering of functional data using pseudo-densities
- Bayesian clustering of functional data using local features
- Empirical dynamics for longitudinal data
- Nonparametric regression analysis of growth curves
- The Riemannian structure of Euclidean shape spaces: A novel environment for statistics
- Large sample theory of intrinsic and extrinsic sample means on manifolds. I
- Linear processes in function spaces. Theory and applications
- Model-based clustering for multivariate functional data
- Principal components for multivariate functional data
- Local half-region depth for functional data
- Data depth for measurable noisy random functions
- Clustering functional data
- Weak convergence and empirical processes. With applications to statistics
- Principal component analysis for functional data on Riemannian manifolds and spheres
- Intrinsic Riemannian functional data analysis for sparse longitudinal observations
- A central limit theorem for extrinsic antimeans and estimation of Veronese-Whitney means and antimeans on planar Kendall shape spaces
- Convergence rates for empirical barycenters in metric spaces: curvature, convexity and extendable geodesics
- Functional data analysis.
- Directions and projective shapes
- Statistical inferences for functional data
- Interpretable functional principal component analysis
- Statistical Shape Analysis, with Applications in R
- Empirical Analysis of an Evolving Social Network
- Joint modelling of paired sparse functional data using principal components
- Functional linear regression with derivatives
- Shape Manifolds, Procrustean Metrics, and Complex Projective Spaces
- On the consistency of procrustean mean shapes
- Differential equation models for statistical functions
- Estimating time‐varying directed gene regulation networks
- Mean size-and-shapes and mean shapes: a geometric point of view
- Principal Modes of Variation for Processes with Continuous Sample Curves
- Functional data analysis in longitudinal settings using smoothing splines
- Nonparametric regression analysis of multivariate longitudinal data
- Functional Principal Component Analysis of Spatiotemporal Point Processes With Applications in Disease Surveillance
- Data-driven regularization of Wasserstein barycenters with an application to multivariate density registration
- Functional Clustering and Identifying Substructures of Longitudinal Data
- Parameter Estimation for Differential Equations: a Generalized Smoothing Approach
- Statistical Analysis of Functions on Surfaces, With an Application to Medical Imaging
- Principal components of random variables with values in a seperable hilbert space
- Fréchet analysis of variance for random objects
- Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
- Estimating Derivatives for Samples of Sparsely Observed Functions, With Application to Online Auction Dynamics
- On the Concept of Depth for Functional Data
- Functional Varying Coefficient Models for Longitudinal Data
- Extrinsic Means and Antimeans
- Localized Functional Principal Component Analysis
- Modelling Function-Valued Stochastic Processes, with Applications to Fertility Dynamics
- OUP accepted manuscript
- On Properties of Functional Principal Components Analysis
- Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles