A nonparametric two-sample test applicable to high dimensional data
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Publication:391926
DOI10.1016/j.jmva.2013.09.004zbMath1278.62059OpenAlexW1986818650MaRDI QIDQ391926
Munmun Biswas, Anil Kumar Ghosh
Publication date: 13 January 2014
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2013.09.004
permutation testsU-statisticsweak law of large numbersinter-point distanceshigh dimensional asymptoticslarge sample distributions
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Cites Work
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- Multivariate nonparametric methods with R. An approach based on spatial signs and ranks.
- A test for the mean vector with fewer observations than the dimension under non-normality
- PCA consistency in high dimension, low sample size context
- A multivariate two-sample test based on the number of nearest neighbor type coincidences
- Multivariate generalizations of the Wald-Wolfowitz and Smirnov two-sample tests
- On a new multivariate two-sample test.
- On distribution-free tests for the multivariate two-sample location-scale model
- On the multivariate runs test
- Reducing multidimensional two-sample data to one-dimensional interpoint comparisons
- A two-sample test for high-dimensional data with applications to gene-set testing
- Multivariate nonparametric tests
- A triangle test for equality of distribution functions in high dimensions
- Multivariate Two-Sample Tests Based on Nearest Neighbors
- Multivariate spatial sign and rank methods
- An Approach to Multivariate Rank Tests in Multivariate Analysis of Variance
- Permutation tests for equality of distributions in high-dimensional settings
- A Quality Index Based on Data Depth and Multivariate Rank Tests
- Geometric Representation of High Dimension, Low Sample Size Data
- An Exact Distribution-Free Test Comparing Two Multivariate Distributions based on Adjacency
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