Robust estimation for correlated observations: two local sensitivity-based downweighting strategies

Robust estimation for correlated observations: two local sensitivity-based downweighting strategies
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相关观测值的稳健估计:两种基于局部敏感性的降权策略

DOI:
10.1007/s00190-009-0361-y
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发表时间:
2010-04
期刊:
影响因子:
4.4
通讯作者:
--
中科院分区:
地球科学1区
文献类型:
--
作者:

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提出了一种相关观测值的迭代抗差估计方法,该方法不需要更新先验相关系数矩阵以减轻计算负担。在所提出的方法中,降权策略的选择起着关键作用。两个局部灵敏度为基础的策略,一个是基于一致的最强大的测试统计量,另一个是基于标准化最小二乘残差,开发和分析。GPS网平差的Monte Carlo模拟结果表明,这两种方法都能有效抵抗离群观测值对参数估计的恶化影响,且降权方法的鲁棒性和计算效率均上级降权方法。
An iterative robust estimation procedure for correlated observations is proposed, in which the a-prior correlation coefficient matrix is not updated to alleviate the computational burden. Selection of the downweighting strategy plays a key role in the proposed method. Two local sensitivity-based strategies, one is based on the uniformly most powerful test statistics, the other is based on the standardized least squares residuals, are developed and analyzed. Monte Carlo simulations in the GPS network adjustment scenario demonstrate that, the two strategies can provide a certain resistance against the deteriorating effect of outlying observations on the parameter estimates; the former downweighting strategy is superior to the latter one, both in terms of robustness and computational efficiency.
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