Automatic Diagonal Loading For Tyler'S Robust Covariance Estimator
2016 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP)(2016)
摘要
An approach of regularizing Tyler's robust M-estimator of the covariance matrix is proposed. We also provide an automatic choice of the regularization parameter in the high-dimensional regime. Simulations show its advantage over the sample covariance estimator and Tyler's M-estimator when data is heavy-tailed and the number of samples is small. Compared with the previous approaches of regularizing Tyler's M-estimator, our approach has a similar performance and a much simpler way of choosing the regularization parameter automatically.
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关键词
high-dimensional statistics,robust estimation
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