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Robust estimation of measurement error covariance

Authors: null Zhao Yuhong; null Gu Zhongwen;

Robust estimation of measurement error covariance

Abstract

Conventional indirect estimations of measurement error covariance are very sensitive to gross errors. A robust indirect algorithm based on Hampel's three-part redescending M-estimators is developed. Credible results can be achieved either with or without the presence of external causes. Two examples are provided to demonstrate the robustness of the proposed method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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