Functional estimation of anisotropic covariance and autocovariance operators on the sphere

DOI10.1214/22-EJS2064MaRDI QIDQ2084469

Alessia Caponera, Matthieu Simeoni, Julien Fageot, Victor M. Panaretos

Publication date: 18 October 2022

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

Full work available at URL: https://arxiv.org/abs/2112.12694

zbMATH Keywords

measurement errorfunctional data analysisrepresenter theoremsparse samplingspherical random field

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Inference from stochastic processes (62Mxx)

Uses Software

• fda (R)
• SciPy
• Healpix
• Python
• Dask

Cites Work

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• From sparse to dense functional data and beyond
• On the Besov regularity of periodic Lévy noises
• Fourier analysis of stationary time series in function space
• Global space-time models for climate ensembles
• From Schoenberg coefficients to Schoenberg functions
• Uniform convergence rates for nonparametric regression and principal component analysis in functional/longitudinal data
• Optimal estimation of the mean function based on discretely sampled functional data: phase transition
• Optimal rates of convergence for nonparametric estimators
• Tensor product space ANOVA models.
• Lasso estimation for spherical autoregressive processes
• Functional penalised basis pursuit on spheres
• Sparsely observed functional time series: estimation and prediction
• A unifying representer theorem for inverse problems and machine learning
• SPHARMA approximations for stationary functional time series on the sphere
• Towards a complete picture of stationary covariance functions on spheres cross time
• Cramér-Karhunen-Loève representation and harmonic principal component analysis of functional time series
• Matérn-based nonstationary cross-covariance models for global processes
• Functional data analysis.
• Properties of principal component methods for functional and longitudinal data analysis
• Some results on Tchebycheffian spline functions and stochastic processes
• Asymptotics for spherical functional autoregressions
• Representer Theorems for Sparsity-Promoting <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math> </inline-formula> Regularization
• Random Fields on the Sphere
• Regularity of Gaussian white noise on the d-dimensional torus
• An Introduction to Sparse Stochastic Processes
• Nonseparable, Stationary Covariance Functions for Space–Time Data
• Continuous-Domain Solutions of Linear Inverse Problems With Tikhonov Versus Generalized TV Regularization
• Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems
• Theory of Ridge Regression Estimation with Applications
• Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
• All of Nonparametric Statistics
• Functional Data Analysis for Sparse Longitudinal Data
• Theory of Reproducing Kernels
• Modeling Temporally Evolving and Spatially Globally Dependent Data

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