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This research aims to provide generalized least squares estimators for evaluating population parameters in correlation matrices.

The analysis of patterned correlation matrices by generalized least squares

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This research aims to provide generalized least squares estimators for evaluating population parameters in correlation matrices.
Developed generalized least squares estimators for population parameters of correlation matrices.
Conducted asymptotic chi-square tests for specified values in correlation matrices.
Provided comparative formulae for covariance matrices.
Generalized least squares estimators are asymptotically equivalent to maximum-likelihood estimators.
The computation required for generalized least squares is less than that for maximum-likelihood estimators.

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Randomized trial examines estimators for correlation matrices, suggesting efficient computation methods.

Michael W. Browne (1977) studied this question.

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