Multi-sample comparison using spatial signs for infinite dimensional data
From MaRDI portal
Publication:2084458
DOI10.1214/22-EJS2054MaRDI QIDQ2084458
Joydeep Chowdhury, Probal Chaudhuri
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/2207.12025
Gaussian processanalysis of variancepermutation testfunctional databootstrap testKruskal-Wallis test\(t\) process
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm
- An introduction to functional data analysis and a principal component approach for testing the equality of mean curves
- A simple multiway ANOVA for functional data
- A comparison of tests for the one-way ANOVA problem for functional data
- An ANOVA test for functional data
- Multivariate nonparametric methods with R. An approach based on spatial signs and ranks.
- \(M\)-estimation, convexity and quantiles
- On the efficiency of multivariate spatial sign and rank tests
- How do bootstrap and permutation tests work?
- An \(L^2\)-norm based ANOVA test for the equality of weakly dependent functional time series
- A new test for functional one-way ANOVA with applications to ischemic heart screening
- Central limit theorems revisited
- Recent developments in high-dimensional inference for multivariate data: parametric, semiparametric and nonparametric approaches
- fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data
- The spatial distribution in infinite dimensional spaces and related quantiles and depths
- Statistical inferences for functional data
- Statistical inferences for linear models with functional responses
- On a Geometric Notion of Quantiles for Multivariate Data
- Multivariate spatial sign and rank methods
- Box-Type Approximations in Nonparametric Factorial Designs
- An Approach to Multivariate Rank Tests in Multivariate Analysis of Variance
- Rank-Based Procedures in Factorial Designs: Hypotheses About Non-Parametric Treatment Effects
- Robustness and Accuracy of Methods for High Dimensional Data Analysis Based on Student’s t-Statistic
- High-dimensional rank-based inference
- A Wilcoxon-Mann-Whitney-type test for infinite-dimensional data
- Asymptotic Permutation Tests in General Factorial Designs
- One‐Way <scp>anova</scp> for Functional Data via Globalizing the Pointwise F‐test
- Use of Ranks in One-Criterion Variance Analysis
- Notes on functional analysis