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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/41664


    Title: Empirical likelihood confidence intervals for the mean of a population containing many zero values
    Authors: Chen, Jiahua;陳順益;Chen, Shun-yi.;Rao, J. N. K.
    Contributors: 淡江大學數學學系
    Date: 2003-03-01
    Issue Date: 2010-01-28
    Publisher: Statistical Society of Canada
    Abstract: If a population contains many zero values and the sample size is not very large, the traditional normal approximation-based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000.
    Relation: Canadian Journal of Statistics 31(1), pp.53-68
    DOI: 10.2307/3315903
    Appears in Collections:[數學學系暨研究所] 期刊論文

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