Unbiased Estimator for a Covariance Matrix Under Two-Step Monotone Incomplete Sample

DOI10.1080/03610926.2012.671881zbMath1462.62331OpenAlexW1968000959MaRDI QIDQ5419670

Shin-ichi Tsukada

Publication date: 11 June 2014

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

Full work available at URL: https://doi.org/10.1080/03610926.2012.671881

zbMATH Keywords

covariance matrixunbiasednessmonotone incomplete sample

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20)

Related Items

Asymptotic properties of a correlation matrix under a two-step monotone incomplete sample, Equivalence testing of mean vector and covariance matrix for multi-populations under a two-step monotone incomplete sample, Asymptotic expansion for distribution of the trace of a covariance matrix under a two-step monotone incomplete sample, Unbiased estimator for a covariance matrix in a three-step monotone incomplete sample

Cites Work

• An asymptotic approximation for EPMC in linear discriminant analysis based on two-step monotone missing samples
• Finite-sample inference with monotone incomplete multivariate normal data. I.
• Finite-sample inference with monotone incomplete multivariate normal data. II
• The Stein phenomenon for monotone incomplete multivariate normal data
• Maximum-likelihood estimation of the parameters of a multivariate normal distribution
• Multivariate data with missing observations
• A note on the maximum likelihood estimators for multivariate normal distribution with monotone data
• Inferences on a normal covariance matrix and generalized variance with monotone missing data
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