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BISWAS, MUNMUN; MUKHOPADHYAY, MINERVA; GHOSH, ANIL K.
Biometrika, 12/2014, Letnik: 101, Številka: 4Journal Article
We propose a multivariate generalization of the univariate two-sample run test based on the shortest Hamiltonian path. The proposed test is distribution-free in finite samples. While most existing two-sample tests perform poorly or are even inapplicable to high-dimensional data, our test can be conveniently used in high-dimension, low-sample-size situations. We investigate its power when the sample size remains fixed and the dimension of the data grows to infinity. Simulated and real dataseis demonstrate our method's superiority over existing nonparametric twosample tests.
