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An exact distribution-free test comparing two multivariate distributions based on adjacency
| Content Provider | CiteSeerX |
|---|---|
| Author | Rosenbaum, Paul R. |
| Abstract | Summary. A new test is proposed comparing two multivariate distributions by using distances between observations. Unlike earlier tests using interpoint distances, the new test statistic has a known exact distribution and is exactly distribution free. The interpoint distances are used to construct an optimal non-bipartite matching, i.e. a matching of the observations into disjoint pairs to minimize the total distance within pairs. The cross-match statistic is the number of pairs containing one observation from the first distribution and one from the second. Distributions that are very different will exhibit few cross-matches. When comparing two discrete distributions with finite support, the test is consistent against all alternatives. The test is applied to a study of brain activation measured by functional magnetic resonance imaging during two linguistic tasks, comparing brains that are impaired by arteriovenous abnormalities with normal controls. A second exact distribution-free test is also discussed: it ranks the pairs and sums the ranks of the cross-matched pairs. |
| File Format | |
| Journal | Journal of the Royal Statistical Society B |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Multivariate Distribution Exact Distribution-free Test Interpoint Distance Arteriovenous Abnormality New Test Statistic Optimal Non-bipartite Matching Brain Activation Finite Support Disjoint Pair Discrete Distribution Total Distance First Distribution Exact Distribution Linguistic Task Cross-match Statistic New Test Second Exact Distribution-free Test Normal Control Cross-matched Pair Functional Magnetic Resonance |
| Content Type | Text |
| Resource Type | Article |
