Outlier detection for high-dimensional data

@inproceedings{Zou2015OutlierDF,
  title={Outlier detection for high-dimensional data},
  author={Changliang Zou and Zhaojun Wang and Guosheng Yin},
  year={2015}
}
Outlier detection is an integral component of statistical modelling and estimation. For highdimensional data, classical methods based on the Mahalanobis distance are usually not applicable. We propose an outlier detection procedure that replaces the classical minimum covariance determinant estimator with a high-breakdown minimum diagonal product estimator. The cut-off value is obtained from the asymptotic distribution of the distance, which enables us to control the Type I error and deliver… CONTINUE READING
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