On high dimensional two-sample tests based on nearest neighbors
From MaRDI portal
Publication:746878
DOI10.1016/j.jmva.2015.07.002zbMath1323.62037OpenAlexW987533453MaRDI QIDQ746878
Pronoy K. Mondal, Munmun Biswas, Anil Kumar Ghosh
Publication date: 21 October 2015
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2015.07.002
law of large numberscentral limit theorempermutation testHDLSS datalevel and power of a testlarge sample test
Related Items (15)
Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients ⋮ A robust and nonparametric two-sample test in high dimensions ⋮ Some clustering-based exact distribution-free \(k\)-sample tests applicable to high dimension, low sample size data ⋮ Hotelling's \(T^2\) in separable Hilbert spaces ⋮ High-dimensional general linear hypothesis testing under heteroscedasticity ⋮ High dimensional two-sample test based on the inter-point distance ⋮ Testing homogeneity in high dimensional data through random projections ⋮ Multivariate goodness-of-fit on flat and curved spaces via nearest neighbor distances ⋮ Linear hypothesis testing in high-dimensional one-way MANOVA ⋮ Robust multivariate nonparametric tests via projection averaging ⋮ A review of 20 years of naive tests of significance for high-dimensional mean vectors and covariance matrices ⋮ A two-sample test for the equality of univariate marginal distributions for high-dimensional data ⋮ Global and local two-sample tests via regression ⋮ Shape-preserving wavelet-based multivariate density estimation ⋮ On some graph-based two-sample tests for high dimension, low sample size data
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A two sample test in high dimensional data
- A nonparametric two-sample test applicable to high dimensional data
- Über die Anzahl von Zufallspunkten mit typ-gleichem nächsten Nachbarn und einen multivariaten Zwei-Stichproben-Test
- 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.
- Optimal tests for the general two-sample problem
- A test for the mean vector in large dimension and small samples
- A two-sample test for high-dimensional data with applications to gene-set testing
- A distribution-free two-sample run test applicable to high-dimensional data
- A triangle test for equality of distribution functions in high dimensions
- On some exact distribution-free one-sample tests for high dimension low sample size data
- Mutual and shared neighbor probabilities: finite- and infinite-dimensional results
- Multivariate Two-Sample Tests Based on Nearest Neighbors
- An Approach to Multivariate Rank Tests in Multivariate Analysis of Variance
- Permutation tests for equality of distributions in high-dimensional settings
- Geometric Representation of High Dimension, Low Sample Size Data
- An Exact Distribution-Free Test Comparing Two Multivariate Distributions based on Adjacency
- A Distribution Free Version of the Smirnov Two Sample Test in the $p$-Variate Case
This page was built for publication: On high dimensional two-sample tests based on nearest neighbors