Modeling spatially dependent functional data via regression with differential regularization

DOI10.1016/j.jmva.2018.09.006zbMath1415.62016OpenAlexW2894651531MaRDI QIDQ1733289

Laura M. Sangalli, Eleonora Arnone, Fabio Nobile, Laura Azzimonti

Publication date: 21 March 2019

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://infoscience.epfl.ch/record/234513/files/Report%2002.2018_EA-LA-FN-LS.pdf

zbMATH Keywords

smoothingfinite elementspartial differential equationpenalized regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Numerical smoothing, curve fitting (65D10) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (10)

Some first results on the consistency of spatial regression with partial differential equation regularization ⋮ A roughness penalty approach to estimate densities over two-dimensional manifolds ⋮ Computationally efficient techniques for spatial regression with differential regularization ⋮ Estimation of spatial-functional based-line logit model for multivariate longitudinal data ⋮ Spatial Regression With Partial Differential Equation Regularisation ⋮ Recent advances in functional data analysis and high-dimensional statistics ⋮ A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions ⋮ Some first inferential tools for spatial regression with differential regularization ⋮ Inference for spatial regression models with functional response using a permutational approach ⋮ Recent developments in complex and spatially correlated functional data

Uses Software

• Gstat
• fda (R)
• gamair
• fdaPDE

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Gstat
• fda (R)
• A universal kriging predictor for spatially dependent functional data of a Hilbert space
• Inference for functional data with applications
• Smooth principal component analysis over two-dimensional manifolds with an application to neuroimaging
• Linear smoothers and additive models
• Model-based geostatistics.
• Cardiovascular mathematics. Modeling and simulation of the circulatory system
• Cokriging for spatial functional data
• Asymptotics for M-type smoothing splines
• Modeling spatial anisotropy via regression with partial differential regularization
• Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics
• Optimal global rates of convergence for nonparametric regression
• IGS: an isogeometric approach for smoothing on surfaces
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Spatial regression models over two-dimensional manifolds
• Parameter Estimation of Partial Differential Equation Models
• Mixed Finite Elements for Spatial Regression with PDE Penalization
• Estimating a Predator‐Prey Dynamical Model with the Parameter Cascades Method
• Multivariate Smoothing Spline Functions
• Introduction to Functional Data Analysis
• Soap Film Smoothing
• Spline Smoothing over Difficult Regions
• Parameter Estimation for Differential Equations: a Generalized Smoothing Approach
• Generalized spatial regression with differential regularization
• Statistics for Spatial Data
• Blood Flow Velocity Field Estimation Via Spatial Regression With PDE Penalization
• Spatial Spline Regression Models

This page was built for publication: Modeling spatially dependent functional data via regression with differential regularization