Empirical likelihood confidence intervals for the mean of a population containing many zero values | |
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學年 | 91 |
學期 | 2 |
出版(發表)日期 | 2003-03-01 |
作品名稱 | Empirical likelihood confidence intervals for the mean of a population containing many zero values |
作品名稱(其他語言) | |
著者 | Chen, Jiahua; 陳順益; Chen, Shun-yi.; Rao, J. N. K. |
單位 | 淡江大學數學學系 |
出版者 | Statistical Society of Canada |
著錄名稱、卷期、頁數 | Canadian Journal of Statistics 31(1), pp.53-68 |
摘要 | 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. |
關鍵字 | |
語言 | en |
ISSN | 0319-5724 |
期刊性質 | 國內 |
收錄於 | |
產學合作 | |
通訊作者 | |
審稿制度 | 否 |
國別 | TWN |
公開徵稿 | |
出版型式 | ,電子版 |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41664 ) |