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Association of zero-inflated continuous variables

Author

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  • Pimentel, Ronald S.
  • Niewiadomska-Bugaj, Magdalena
  • Wang, Jung-Chao

Abstract

Zero-inflated continuous distributions are used for modeling in many research areas such as health, environment, or insurance. Since classical estimator of Kendall’s τ becomes biased when applied to such data, we propose an estimator that has a smaller bias and better coverage probability.

Suggested Citation

  • Pimentel, Ronald S. & Niewiadomska-Bugaj, Magdalena & Wang, Jung-Chao, 2015. "Association of zero-inflated continuous variables," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 61-67.
    • Handle: RePEc:eee:stapro:v:96:y:2015:i:c:p:61-67
    DOI: 10.1016/j.spl.2014.09.002
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    References listed on IDEAS

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    1. Douglas J. Taylor & Lawrence L. Kupper & Stephen M. Rappaport & Robert H. Lyles, 2001. "A Mixture Model for Occupational Exposure Mean Testing with a Limit of Detection," Biometrics, The International Biometric Society, vol. 57(3), pages 681-688, September.
    2. Denuit, Michel & Lambert, Philippe, 2005. "Constraints on concordance measures in bivariate discrete data," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 40-57, March.
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    Cited by:

    1. Denuit, Michel & Mesfioui, Mhamed, 2016. "Bounds on Kendall’s Tau for Zero-Inflated Continuous Variables," LIDAM Discussion Papers ISBA 2016043, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Perrone, Elisa & van den Heuvel, Edwin R. & Zhan, Zhuozhao, 2023. "Kendall’s tau estimator for bivariate zero-inflated count data," Statistics & Probability Letters, Elsevier, vol. 199(C).
    3. Denuit, Michel M. & Mesfioui, Mhamed, 2017. "Bounds on Kendall’s tau for zero-inflated continuous variables," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 173-178.

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