2004Journal of China Institute of MetrologyRequires access

The robustness data processing method about eliminating outlier

Honghua Lin

Open publisher page 1 citations

Abstract

Because the methods to eliminate outlier in the past, including the criterion of outlier given in the national standard GB8056-87 and GB6380-86, which often utilized residuals and standard deviation, and was based on a certain typical probability distribution assumption, there was their limitation on it. And these methods may be affected by outlier at the beginning of discrimination, especially in small sample situation misjudge was occurred. In this paper, a universal robustness method to eliminate outlier was proposed according to kinds of simulation experiments by the author, and expected to be adopted in small sample data of variant probability distribution.

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What this paper is about

Because the methods to eliminate outlier in the past, including the criterion of outlier given in the national standard GB8056-87 and GB6380-86, which often utilized residuals and standard deviation, and was based on a certain typical probability distribution assumption, there was their limitation on it. And these methods may be affected by outlier at the beginning of discrimination, especially in small sample situation misjudge was occurred. In this paper, a universal robustness method to eliminate outlier was proposed according to kinds of simulation experiments by the author, and expected to be adopted in small sample data of variant probability distribution.

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Available abstract

Because the methods to eliminate outlier in the past, including the criterion of outlier given in the national standard GB8056-87 and GB6380-86, which often utilized residuals and standard deviation, and was based on a certain typical probability distribution assumption, there was their limitation on it. And these methods may be affected by outlier at the beginning of discrimination, especially in small sample situation misjudge was occurred. In this paper, a universal robustness method to eliminate outlier was proposed according to kinds of simulation experiments by the author, and expected to be adopted in small sample data of variant probability distribution.

Key concepts: Outlier, Robustness (evolution), Standard deviation, Anomaly detection, Sample mean and sample covariance, Statistics, Computer science, Probability distribution

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