Covariance estimation under missing observations and L4 − L2 moment equivalence
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Author
Date
2024Type
- Journal Article
ETH Bibliography
yes
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Abstract
We consider the problem of estimating the covariance matrix of a random vector by observing i.i.d samples, where entry of the sampled vector is missing with probability p. Under the standard L4 - L2 moment equivalence assumption, we construct the first estimator that simultaneously achieves optimality with respect to the parameter p and recovers the optimal convergence rate for the classical covariance estimation problem when p = 1. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000682587Publication status
publishedExternal links
Journal / series
Electronic Journal of StatisticsVolume
Pages / Article No.
Publisher
Institute of Mathematical StatisticsSubject
Covariance estimation; missing observations; heavy tailsOrganisational unit
09679 - Bandeira, Afonso / Bandeira, Afonso
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Is new version of: https://doi.org/10.3929/ethz-b-000655260
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ETH Bibliography
yes
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