Estimation of the covariance matrix with two-step monotone missing data

DOI10.1080/03610926.2013.868085zbMath1341.62120OpenAlexW2088023165MaRDI QIDQ2811403

Nobumichi Shutoh, Takashi Seo, Tatjana Pavlenko, Masashi Hyodo

Publication date: 10 June 2016

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2013.868085

zbMATH Keywords

high-dimensional estimationmonotone missing data

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12)

Cites Work

• Unnamed Item
• A well-conditioned estimator for large-dimensional covariance matrices
• An asymptotic approximation for EPMC in linear discriminant analysis based on two-step monotone missing samples
• Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data
• Maximum-likelihood estimation of the parameters of a multivariate normal distribution
• Some one-sample hypothesis testing problems when there is a monotone sample from a multivariate normal population
• Some Basic Properties of the Mle's for a Multivariate Normal Distribution with Monotone Missing Data

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