| Confidence intervals for the mean of a population containing many zero values under unequal-probability sampling | |
|---|---|
| 學年 | 99 |
| 學期 | 1 |
| 出版(發表)日期 | 2010-12-01 |
| 作品名稱 | Confidence intervals for the mean of a population containing many zero values under unequal-probability sampling |
| 作品名稱(其他語言) | |
| 著者 | Chen, Hanfeng; Chen, Jiahua; Chen, Shun-Yi |
| 單位 | 淡江大學數學學系 |
| 出版者 | Hoboken: Wiley-Blackwell Publishing, Inc. |
| 著錄名稱、卷期、頁數 | The Canadian Journal of Statistics 38(4), pp.582-597 |
| 摘要 | In many applications, a finite population contains a large proportion of zero values that make the population distribution severely skewed. An unequal-probability sampling plan compounds the problem, and as a result the normal approximation to the distribution of various estimators has poor precision. The central-limit-theorem-based confidence intervals for the population mean are hence unsatisfactory. Complex designs also make it hard to pin down useful likelihood functions, hence a direct likelihood approach is not an option. In this paper, we propose a pseudo-likelihood approach. The proposed pseudo-log-likelihood function is an unbiased estimator of the log-likelihood function when the entire population is sampled. Simulations have been carried out. When the inclusion probabilities are related to the unit values, the pseudo-likelihood intervals are superior to existing methods in terms of the coverage probability, the balance of non-coverage rates on the lower and upper sides, and the interval length. An application with a data set from the Canadian Labour Force Survey-2000 also shows that the pseudo-likelihood method performs more appropriately than other methods. |
| 關鍵字 | Accounting; inclusion probability; mixture models; pseudo-likelihood; stratified sampling; survey sampling; zero-inflated data |
| 語言 | en |
| ISSN | 1708-945X |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | |
| 國別 | USA |
| 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/987654321/64129 ) |