Nonparametric interval estimation for the mean of a zero-inflated population

References

• Chen, B. B., G. M. Pan, Q. Yang, and W. Zhou. 2015. Large dimensional empirical likelihood. Statistica Sinica 25:1659–1677.
   Web of Science ®Google Scholar
• Chen, J., S.-Y. Chen, and J. N. K. Rao. 2003. Empirical likelihood confidence intervals for the mean of a population containing many zero values. Canadian Journal of Statistics 31 (1):53–68.
   Web of Science ®Google Scholar
• Chen, J., A. Mulayath, and B. Abraham. 2008. Adjusted empirical likelihood and its properties. Journal of Computational and Graphical Statistics 17 (2):426–443.
   Web of Science ®Google Scholar
• Chen, S. X., and J. Qin. 2003. Empirical likelihood-based confidence intervals for data with possible zero observations. Statistics and Probability Letters 65 (1):29–37.
   Web of Science ®Google Scholar
• Cheng, C. H., Y. Liu, Z. Liu, and W. Zhou. 2018. Balanced augmented jackknife empirical likelihood for two sample U-statistics. Science China Mathematics 61 (6):1129–1138.
   Web of Science ®Google Scholar
• Corcoran, S. 1998. Bartlett adjustment of empirical discrepancy statistics. Biometrika 85 (4):967–972.
   Web of Science ®Google Scholar
• DiCiccio, T., P. Hall, and J. Romano. 1991. Empirical likelihood is bartlett-correctable. The Annals of Statistics 19 (2):1053–1061.
   Web of Science ®Google Scholar
• Dobbie, M. J., and A. H. Welsh. 2001. Modelling correlated zero-inflated count data. Australian and New Zealand Journal of Statistics 43 (4):431–444.
   Web of Science ®Google Scholar
• Fletcher, D., D. MacKenzie, and E. Villouta. 2005. Modelling skewed data with many zeros: a simple approach combining ordinary and logistic regression. Environmental and Ecological Statistics 12 (1):45–54.
   Web of Science ®Google Scholar
• Hall, D. B. 2000. Zero-inflated poisson and binomial regression with random effects: a case study. Biometrics 56 (4):1030–1039.
   PubMed Web of Science ®Google Scholar
• Hall, P., and B. La Scala. 1990. Methodology and algorithms of empirical likelihood. International Statistical Review 58 (2):109–127.
   Web of Science ®Google Scholar
• Hu, M.-C., M. Pavlicova, and E. V. Nunes. 2011. Zero-inflated and hurdle models of count data with extra zeros: examples from an HIV-Risk Reduction intervention trial. The American Journal of Drug and Alcohol Abuse 37 (5):367–375.
   PubMed Web of Science ®Google Scholar
• Jing, B., J. Yuan, and W. Zhou. 2009. Jackknife empirical likelihood. Journal of the American Statistical Association 104 (487):1224–1232.
   Web of Science ®Google Scholar
• Kang, L., A. Vexler, L. Tian, M. Cooney, B. Louis, and M. Germaine. 2010. Empirical and parametric likelihood interval estimation for populations with many zero values: application for assessing environmental chemical concentrations and reproductive health. Epidemiology 21:S58–S63.
   PubMed Web of Science ®Google Scholar
• Lambert, D. 1992. Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics 34 (1):1–14.
   Web of Science ®Google Scholar
• Liu, Y., and J. Chen. 2010. Adjusted empirical likelihood with high-order precision. The Annals of Statistics 38 (3):1341–1362.
   Web of Science ®Google Scholar
• Min, Y., and A. Agresti. 2002. Modeling nonnegative data with clumping at zero: a survey. Journal of the Iranian Statistical Society 1 (1-2):7–33.
   Google Scholar
• Owen, A. B. 1988. Empirical likelihood ratio confidence intervals for a single functional. Biometrika 75 (2):237–249.
   Web of Science ®Google Scholar
• Owen, A. 1990. Empirical likelihood ratio confidence regions. The Annals of Statistics 18 (1):90–120.
   Web of Science ®Google Scholar
• Owen, A. B. 2001. Empirical likelihood. New York, NY: Chapman & Hall/CRC.
   Google Scholar
• Pailden, J., and H. Chen. 2013. Empirical likelihood ratio test for difference of the means of zero-inflated populations. Advances and Applications in Statistics 35 (1):29–55.
   Google Scholar
• Tang, W., H. He, and X. M. Tu. 2012. Applied categorical and count data analysis. New York, NY: Chapman & Hall/CRC.
   Google Scholar
• Wang, D., and Y. Zhao. 2016. Jackknife empirical likelihood for comparing two Gini indices. Canadian Journal of Statistics 44 (1):102–119.
   Web of Science ®Google Scholar
• Welsh, A. H., R. B. Cunningham, C. F. Donnelly, and D. B. Lindenmayer. 1996. Modelling the abundance of rare species: statistical models for counts with extra zeros. Ecological Modelling 88 (1-3):297–308.
   Web of Science ®Google Scholar
• Zhao, Y., X. Meng, and H. Yang. 2015. Jackknife empirical likelihood inference for the mean absolute deviation. Computational Statistics and Data Analysis 91:92–101.
   Web of Science ®Google Scholar
• Zhou, X. H., and W. Tu. 2000. Confidence intervals for the mean of diagnostic test charge data containing zeros. Biometrics 56 (4):1118–1125.
   PubMed Web of Science ®Google Scholar
• Zhou, W., and Z. Xiao-Hua. 2005. Empirical likelihood intervals for the mean difference of two skewed populations with additional zero values. UW Biostatistics Working Paper Series. Working Paper 246. http://biostats.bepress.com/uwbiostat/paper246.
   Google Scholar