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Likelihood-based Inference for the Ratios of Regression Coefficients in Linear Models

โœ Scribed by Malay Ghosh; Gauri Sankar Datta; Dalho Kim; Trevor J. Sweeting


Publisher
Springer Japan
Year
2006
Tongue
English
Weight
200 KB
Volume
58
Category
Article
ISSN
0020-3157

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The existing algorithms for fitting the random coefficient models tend to have difficulties associated with the covariance matrix parameter space. New ML and REML algorithms are developed, explicitly addressing the parameter space problem. Theoretical justification and numerical results are presente