Invariance properties of dependence measures
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Title Invariance properties of dependence measures
Creator Atiwat Kitvanitphasu
Contributor Songkiat Sumetkijakan
Publisher Chulalongkorn University
Publication Year 2558
Keyword Copulas (Mathematical statistics), Probabilities, Measure theory, คอปูลา (คณิตศาสตร์สถิติ), ความน่าจะเป็น, ทฤษฎีการวัด
Abstract Li gave a generalization of non-symmetric copula-based dependence measure, such as the Trutschnig\'s measure of dependence. A precise sufficient condition which makes Li\'s generalization a non-symmetric measure of dependence is given and proved rigorously. Supported by its non-symmetric dependence measure properties, we symmetrize the Li\'s non-symmetric measure of dependence and investigate its properties. Specifically, we analyze the key properties of dependence measures including well-defined property, abilities to detect independence and dependence at the two extreme values $0,1$ respectively, and invariance under the certain types of transformations. In particular, we find, via several examples, that a dependence measure possessing an ability to detect a larger class of dependences tends to be invariant under an accordingly large class of transformations. The probabilistic version of maximal information coefficient (MIC) is also proved to be a dependence measure. Lastly, we show that there does not exist a dependence measure which is both invariant under strictly monotonic transformations and able to catch complete dependence.
URL Website cuir.car.chula.ac.th
Chulalongkorn University

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