Technometrics · 1973 · 131 citations · 5 references
BusinessComputational EngineeringOptimizationStatistical ModelingStochastic ModelingLikelihood ComputationLikelihood EstimationMatrix ComputationMaximum Likelihood EstimationMixed Model AnalysisParameter EstimationCovariance Structure ModelingExpectation-maximization AlgorithmIterative Maximum Likelihood AlgorithmsMaximum Likelihood InferenceMixed Model EquationsVariance Component EstimationVariance Components AnalysisVariance-covariance Matrix Estimation
The W transformation, a matrix transformation, is developed and applied for the mixed analysis of variance model to compute maximum likelihood estimates of the variance components and fixed parameters. This transformation not only eliminates the need for the explicit computation of the n × n inverse matrix H−l but permits handling the iterative calculations such that they do not depend upon n (the number of observations) in any way. Although not wedded to a particular numerical method, the W transformation is implemented in conjunction with a modified Newton-Raphson method in which variance components are restricted to being non-negative.
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Statistical Papers in Honor of George W. Snedecor
G. G. K. · Technometrics · 1973 · 63 citations
W. R. Buckland, A. H. Bowker, G. J. Lieberman · Biometrika · 1962 · 14 citations