期刊論文
| 學年 | 94 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2005-08-01 |
| 作品名稱 | Comparison of Normal Variance Estimators under Multiple Criteria and Towards a Compromise Estimator |
| 作品名稱（其他語言） | |
| 著者 | Lin, Jyh-Jiuan; Pal, Nabendu |
| 單位 | 淡江大學統計學系 |
| 出版者 | Abingdon: Taylor & Francis |
| 著錄名稱、卷期、頁數 | Journal of Statistical Computation and Simulation 75(8), pp.645-665 |
| 摘要 | For estimating a normal variance under the squared error loss function it is well known that the best affine (location and scale) equivariant estimator, which is better than the maximum likelihood estimator as well as the unbiased estimator, is also inadmissible. The improved estimators, e.g., stein type, brown type and Brewster–Zidek type, are all scale equivariant but not location invariant. Lately, a good amount of research has been done to compare the improved estimators in terms of risk, but comparatively less attention had been paid to compare these estimators in terms of the Pitman nearness criterion (PNC) as well as the stochastic domination criterion (SDC). In this paper, we have undertaken a comprehensive study to compare various variance estimators in terms of the PNC and the SDC, which has been long overdue. Finally, using the results for risk, the PNC and the SDC, we propose a compromise estimator (sort of a robust estimator) which appears to work ‘well’ under all the criteria discussed above. |
| 關鍵字 | Affine equivariance; Risk function; chi-square distribution |
| 語言 | en |
| ISSN | 0094-9655 1563-5163 |
| 期刊性質 | 國外 |
| 收錄於 | SCI SSCI EI |
| 產學合作 | |
| 通訊作者 | Lin, Jyh-Jiuan |
| 審稿制度 | 是 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | 紙本 電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98648 ) |