Missing data in the k-population multivariate normal patterned mean and covariance matrix testing and estimation problem
DOI10.1080/03610918508812444zbMath0606.62055OpenAlexW2085651400MaRDI QIDQ3745072
Publication date: 1985
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918508812444
EM algorithmlikelihood ratio statisticsdelta methodmissing dataNewton-Raphson algorithmmultivariate normalasymptotic nonnull distributionsMaximum likelihood estimatesscoring algorithmk- population testing and estimation problempatterned means and covariance matrices
Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Hypothesis testing in multivariate analysis (62H15)
Cites Work
- Missing data in the one-population multivariate normal patterned mean and covariance matrix testing and estimation problem
- Asymptotic nonnull distributions for likelihood ratio statistics in the multivariate normal patterned mean and covariance matrix testing problem
- Relative efficiencies of estimates using patterned covariances or correlations in the multivariate normal estimation problem
- 6 Equating Test Scores
- Testing Compound Symmetry in a Normal Multivariate Distribution
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