Manuscript.pdf

1507.08377v1.pdf
Preview of Manuscript
🔗 Source: arxiv.org
📊 Size: 632 KB
📄 Pages: 48 pages
⬇️ Downloads: 82

Summary

We proposed a general Principal Orthogonal complEment Thresholding (POET) framework for large-scale covariance matrix estimation based on an approximate factor model, allowing us to recover results for sub-Gaussian data and extend them to heavy-tailed distributions, specifically elliptical data, using a robust estimator based on marginal and multivariate Kendall’s tau.

Description

We proposed a general Principal Orthogonal complEment Thresholding (POET) framework for large-scale covariance matrix estimation based on an approximate factor...

Technical Information

  • File Format: PDF
  • File Size: 632 KB
  • Pages: 48
  • Language: EN
  • Total Downloads: 82
  • Last Updated: 4 weeks ago

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