Title: Maximum likelihood estimation for multivariate normal distribution with monotone sample
Abstract: Abstract Closed forms are obtained for the maximum likelihood estimators of the mean vector and the covariance matrix of a multivariate normal model with a k-step monotone missing data pattern. Matrix derivatives are used in the derivation. Our results extend those of Anderson and Olkin (1985) for the 2-step missing data pattern. Keywords: multivariate normalmissing datamonotone samplemaximum likelihood estimationmatrix derivatives
Publication Year: 1992
Publication Date: 1992-01-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 36
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