• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国政府科技报告 >Efficient Unbiased Quantile Estimators for Moderate-Size Complete Samples from Extreme-Value and Weibull Distributions: Confidence Bounds and Tolerance and Prediction Intervals.
【24h】

Efficient Unbiased Quantile Estimators for Moderate-Size Complete Samples from Extreme-Value and Weibull Distributions: Confidence Bounds and Tolerance and Prediction Intervals.

机译：针对极值和威布尔分布的中等大小完整样本的高效无偏分位数估计：置信区间和容差以及预测区间。

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Tables of factors are given for complete samples of size n(n=20(1)40) for correcting small-sample bias in Hassanein's asymptotically unbiased quantile estimators of extreme-value location and scale parameters, Hassanein's k-order-statistic estimators of the two parameters are based on the same set of spacings for each k(k=2, ..., 10) and are asymptotically best of this type of linear estimator (with asymptotic efficiencies of .977 and .937, respectively, for k=10). The tabulated values not only allow one to obtain estimates based on the specified set of ordered observations that are best linear unbiased or best linear invariant (for the specified set of weights), but they also enable one to use procedures described in Mann, Schafer, and Singpurwalla to compute approximate confidence bounds and tolerance and prediction intervals. Also tabulated are efficiences of unbiased versions of the estimators relative to Cramer-Rao bounds for regular unbiased estimators and to best linear unbiased estimators (where available). The efficiences of the ten-order-statistic unbiased estimators relative to the best linear unbiased estimators (compared for samples of sizes 20 through 25) are very close to 1. (Author)

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号