Non-asymptotic rate for high-dimensional covariance estimation with non-independent missing observations

Seongoh Park and Johan Lim

Statistics & Probability Letters, 2019, vol. 153, issue C, 113-123

Abstract: In this paper, we study non-asymptotic convergence rate of the inverse probability weight estimator of covariance matrix when some values of the data are missing completely at random.

Keywords: Convergence rate; Covariance matrix; Inverse probability weight estimator; Missing completely at random (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2019.06.002

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