Confidence estimation using dependent circular block bootstrapping: application to the statistical analysis of PIV measurements
Confidence estimation using dependent circular block bootstrapping: application to the statistical analysis of PIV measurements
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DOI：
10.1007/s00348-007-0418-8
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发表时间：
2008-04-01
影响因子：
2.4
通讯作者：
Van den Braembussche, R. A.
中科院分区：
文献类型：
--
作者：
Theunissen, R.;Di Sante, A.;Van den Braembussche, R. A.
在本文中，作者展示了一种现有的确定置信水平和误差的方法的原始应用于时间分辨PIV，称为依赖自举。由于采样频率高，测得的速度样本不再不相关，使得经典的统计方法不再适用。实例表明，基于自相关函数计算独立样本数的各种方法对文献中很少提及的置信水平的可靠性提出了质疑。相反，依赖自举技术报告了相关和不相关PIV速度样本的一致置信度估计结果，使该技术具有鲁棒性和一般性，可用于进一步应用。给出了相关圆块引导实现的逐步描述。通过两个实验实例说明了该方法的实际应用和可行性。
In this paper the authors show an original application to time-resolved PIV of an existing method for confidence level and error determination, called dependent bootstrapping. Due to the high sampling frequencies the measured velocity samples are no longer uncorrelated making classical statistical procedures not applicable. Examples show that the various ways in calculating the number of independent samples based on the autocorrelation function question the reliability of the rarely, if ever, mentioned confidence levels in literature. Instead, the dependent bootstrapping technique reports consistent results of confidence estimates for both correlated and uncorrelated PIV velocity samples making this technique robust and general for further applications. The step-by-step description of the dependent circular block bootstrap implementation is given. The practical application and viability of the method are illustrated by two experimental cases.