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Nonnegative Minimum Biased Quadratic Estimation in Mixed Linear Models

✍ Scribed by Stanisław Gnot; Mariusz Grzadziel

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
149 KB
Volume
80
Category
Article
ISSN
0047-259X

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✦ Synopsis

The problem of nonnegative quadratic estimation of a parametric function

Necessary and sufficient conditions are given for y$A 0 y to be a minimum biased estimator for #. It is shown how to formulate the problem of finding a nonnegative minimium biased estimator of # as a conic optimization problem, which can be efficiently solved using convex optimization techniques. Models with two variance components are considered in detail. Some applications to one-way classification mixed models are given. For these models minimum biased estimators with minimum norms for square of expectation ; 2 and for _ 2 1 are presented in explicit forms.

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