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Comparisons on Measures of Asymmetric Associations

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Beyond Traditional Probabilistic Methods in Economics (ECONVN 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 809))

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Abstract

In this paper, we review some recent contributions to multivariate measures of asymmetric associations, i.e., associations in an n-dimension random vector, where \(n >1\). Specially, we pay more attention on measures of complete dependence (or functional dependence). Nonparametric estimators of several measures are provided and comparisons among several measures are given.

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Author information

Authors and Affiliations

  1. Department of Mathematical Sciences, New Mexico State University, Las Cruces, USA

    Xiaonan Zhu & Tonghui Wang

  2. Department of Information System, College of Information Engineering, Northwest A & F University, Yangling, China

    Xiaoting Zhang

  3. School of Mathematics and Statistics, Xidian University, Xian, China

    Liang Wang

Authors
  1. Xiaonan Zhu
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  2. Tonghui Wang
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  3. Xiaoting Zhang
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  4. Liang Wang
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Corresponding author

Correspondence to Tonghui Wang .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

  3. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Duc Trung

  4. TTC Group, Ho Chi Minh City, Vietnam

    Dang Van Thanh

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Zhu, X., Wang, T., Zhang, X., Wang, L. (2019). Comparisons on Measures of Asymmetric Associations. In: Kreinovich, V., Thach, N., Trung, N., Van Thanh, D. (eds) Beyond Traditional Probabilistic Methods in Economics. ECONVN 2019. Studies in Computational Intelligence, vol 809. Springer, Cham. https://doi.org/10.1007/978-3-030-04200-4_15

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