Random Permutations, Non-Decreasing Subsequences and Statistical Independence
In this paper, we show how the longest non-decreasing subsequence, identified in the graph of the paired marginal ranks of the observations, allows the construction of a statistic for the development of an independence test in bivariate vectors. The test works in the case of discrete and continuous...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/12/9/1415 |
| Summary: | In this paper, we show how the longest non-decreasing subsequence, identified in the graph of the paired marginal ranks of the observations, allows the construction of a statistic for the development of an independence test in bivariate vectors. The test works in the case of discrete and continuous data. Since the present procedure does not require the continuity of the variables, it expands the proposal introduced in <i>Independence tests for continuous random variables based on the longest increasing subsequence (2014)</i>. We show the efficiency of the procedure in detecting dependence in real cases and through simulations. |
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| ISSN: | 2073-8994 |