首页> 外文会议>IEEE Statistical Signal Processing Workshop >Mean square error performance of sample mean and sample median estimators
【24h】

Mean square error performance of sample mean and sample median estimators

机译:样本均值和样本中位数估计量的均方误差性能

获取原文

摘要

Based on the Ziv-Zakai methodology to bound estimators, we derived an estimation bound able to predict the mean square error degradation due to model mismatches. In this article, we build upon this result to provide a performance comparison between mean and median estimators in the presence of outliers. The latter is well known to be statistically more robust than the mean in the presence of outliers. Here we show this superiority by comparing their theoretical error bounds. Analytical results are obtained, which are validated by computer simulations.
机译:基于Ziv-Zakai方法对边界估计量的估计,我们得出了一个估计边界,该边界能够预测由于模型不匹配而导致的均方误差降低。在本文中,我们将基于此结果在存在异常值的情况下提供均值和中值估计量之间的性能比较。众所周知,后者在统计上比存在异常值时的均值要强。在这里,我们通过比较它们的理论误差范围来显示这种优势。获得了分析结果,并通过计算机仿真对其进行了验证。

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