Interpoint-ranking sign covariance for the test of independence
| Autor: | Haeun Moon, Kehui Chen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Applied Mathematics General Mathematics 020206 networking & telecommunications 02 engineering and technology Covariance 01 natural sciences Agricultural and Biological Sciences (miscellaneous) Ranking (information retrieval) Test (assessment) 010104 statistics & probability Statistics 0202 electrical engineering electronic engineering information engineering Independence (mathematical logic) 0101 mathematics Statistics Probability and Uncertainty General Agricultural and Biological Sciences Mathematics Sign (mathematics) |
| Zdroj: | Biometrika. 109:165-179 |
| ISSN: | 1464-3510 0006-3444 |
| Popis: | Summary We generalize the sign covariance introduced by Bergsma & Dassios (2014) to multivariate random variables and beyond. The new interpoint-ranking sign covariance is applicable to general types of random objects as long as a meaningful similarity measure can be defined, and it is shown to be zero if and only if the two random variables are independent. The test statistic is a $U$-statistic, whose large-sample behaviour guarantees that the proposed test is consistent against general types of alternatives. Numerical experiments and data analyses demonstrate the superior empirical performance of the proposed method. |
| Databáze: | OpenAIRE |
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