Performance analysis of Tyler's covariance estimator

Ilya Soloveychik, Ami Wiesel

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


This paper analyzes the performance of Tyler's M-estimator of the scatter matrix in elliptical populations. We focus on the non-asymptotic setting and derive estimation error bounds depending on the number of samples n and the dimension p. We show that under mild conditions the squared Frobenius norm of the error of the inverse estimator decays like p2/n with high probability.

Original languageAmerican English
Article number6971237
Pages (from-to)418-426
Number of pages9
JournalIEEE Transactions on Signal Processing
Issue number2
StatePublished - 15 Jan 2015

Bibliographical note

Publisher Copyright:
© 2014 IEEE.


  • Concentration bounds
  • Tyler's scatter estimator
  • elliptical distribution shape matrix estimation
  • scatter matrix M-estimators


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