Restricted expected multivariate least squares
A new approach of estimating parameters in multivariate models is introduced. A fitting function will be used. The idea is to estimate parameters so that the fitting function equals or will be close to its expected value. The function will be decomposed into two parts. From one part, which will be independent of the mean parameters, the dispersion matrix is estimated. This estimator is inserted in the second part which then yields the estimators of the mean parameters. The Growth Curve model, extended Growth Curve model and a multivariate variance components model will illustrate the approach.
Year of publication: |
2006
|
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Authors: | Fang, Kai-Tai ; Wang, Song-Gui ; von Rosen, Dietrich |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 97.2006, 3, p. 619-632
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Publisher: |
Elsevier |
Keywords: | Estimators Growth curve model Extended growth curve model Least squares Variance components REMLS |
Saved in:
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