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Interval estimation for the mean of lognormal data with excess zeros

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  • Li, Xinmin
  • Zhou, Xiaohua
  • Tian, Lili

Abstract

This paper considered interval estimations for the mean of lognormal distribution with excess zeros. We proposed two methods for interval estimation based on an approximate generalized pivotal quantity and a fiducial quantity. Simulation results show that the fiducial approach has highly accurate coverage probability and fairly low bias.

Suggested Citation

  • Li, Xinmin & Zhou, Xiaohua & Tian, Lili, 2013. "Interval estimation for the mean of lognormal data with excess zeros," Statistics & Probability Letters, Elsevier, vol. 83(11), pages 2447-2453.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:11:p:2447-2453
    DOI: 10.1016/j.spl.2013.07.004
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    References listed on IDEAS

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    1. Zou, Guang Yong & Taleban, Julia & Huo, Cindy Y., 2009. "Confidence interval estimation for lognormal data with application to health economics," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3755-3764, September.
    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.
    3. Jan Hannig & Thomas C. M. Lee, 2009. "Generalized fiducial inference for wavelet regression," Biometrika, Biometrika Trust, vol. 96(4), pages 847-860.
    4. Hannig, Jan & Iyer, Hari & Patterson, Paul, 2006. "Fiducial Generalized Confidence Intervals," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 254-269, March.
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