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Empirical likelihood-based confidence intervals for data with possible zero observations

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  • Chen, Song Xi
  • Qin, Jing

Abstract

In statistical applications, we often encounter a situation where a substantial number of observations takes zero value and at the same time the non-zero observations are highly skewed. We propose empirical likelihood-based non-parametric confidence intervals for the mean parameter which have two unique features. One is that the information contained in the zero observations is fully utilized. The other is that the proposed confidence intervals are more reflective to the skewness in the non-zero observations than those based on the asymptotic normality.

Suggested Citation

  • Chen, Song Xi & Qin, Jing, 2003. "Empirical likelihood-based confidence intervals for data with possible zero observations," Statistics & Probability Letters, Elsevier, vol. 65(1), pages 29-37, October.
    • Handle: RePEc:eee:stapro:v:65:y:2003:i:1:p:29-37
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    References listed on IDEAS

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    1. Song Chen, 1993. "On the accuracy of empirical likelihood confidence regions for linear regression model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(4), pages 621-637, December.
    2. Xiao-Hua Zhou & Wanzhu Tu, 2000. "Confidence Intervals for the Mean of Diagnostic Test Charge Data Containing Zeros," Biometrics, The International Biometric Society, vol. 56(4), pages 1118-1125, December.
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    Cited by:

    1. Gengsheng Qin & Baoying Yang & Nelly Belinga-Hall, 2013. "Empirical likelihood-based inferences for the Lorenz curve," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 1-21, February.
    2. Taylor Sandra & Pollard Katherine, 2009. "Hypothesis Tests for Point-Mass Mixture Data with Application to `Omics Data with Many Zero Values," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-43, February.
    3. Mariana Rodrigues-Motta & Johannes Forkman, 2022. "Bayesian Analysis of Nonnegative Data Using Dependency-Extended Two-Part Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 201-221, June.
    4. Wang, Chunlin & Marriott, Paul & Li, Pengfei, 2018. "Semiparametric inference on the means of multiple nonnegative distributions with excess zero observations," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 182-197.

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