The interval testing procedure: A general framework for inference in functional data analysis

DOI10.1111/biom.12476zbMath1390.62298OpenAlexW2252403575WikidataQ31039965 ScholiaQ31039965MaRDI QIDQ2827195

Simone Vantini, Alessia Pini

Publication date: 12 October 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.12476

zbMATH Keywords

inferencefunctional data analysismultiple comparisonfamily wise error ratepermutation method

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (16)

Two-sample tests for multivariate functional data with applications ⋮ Unnamed Item ⋮ Statistical inference for stochastic processes: two-sample hypothesis tests ⋮ Gaussian graphical modeling for spectrometric data analysis ⋮ Hotelling's \(T^2\) in separable Hilbert spaces ⋮ Validation of community robustness ⋮ A two-sample test for mean functions with increasing number of projections ⋮ Local inference for functional linear mixed models ⋮ Functional regression models: Some directions of future research ⋮ Recent advances in functional data analysis and high-dimensional statistics ⋮ Multi-aspect local inference for functional data: analysis of ultrasound tongue profiles ⋮ Nonparametric inference for functional‐on‐scalar linear models applied to knee kinematic hop data after injury of the anterior cruciate ligament ⋮ A novel framework for joint sparse clustering and alignment of functional data ⋮ Inferential procedures for partially observed functional data ⋮ fdatest ⋮ Interval-wise testing for functional data

Uses Software

• R

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Pairwise comparison of treatment levels in functional analysis of variance with application to erythrocyte hemolysis
• Inference for functional data with applications
• An ANOVA test for functional data
• No effect and lack-of-fit permutation tests for functional regression
• Estimation and inference in functional mixed-effects models
• Applied functional data analysis. Methods and case studies
• Some high-dimensional tests for a one-way MANOVA
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Testing in mixed-effects FANOVA models
• Likelihood Ratio Tests for Dependent Data with Applications to Longitudinal and Functional Data Analysis
• Permutation tests for equality of distributions in high-dimensional settings
• Test of Significance When Data Are Curves
• A Case Study in Exploratory Functional Data Analysis: Geometrical Features of the Internal Carotid Artery
• Interval-wise testing for functional data
• One‐Way <scp>anova</scp> for Functional Data via Globalizing the Pointwise F‐test

This page was built for publication: The interval testing procedure: A general framework for inference in functional data analysis