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Contents of PMS, Vol. 40, Fasc. 1,
pages 105 - 118
DOI: 10.37190/0208-4147.40.1.7
Published online 8.4.2020
 

An explicit characterization of admissible linear estimators of fixed and random effects in balanced random models

Ewa Synówka-Bejenka
Stefan Zontek

Abstract: A necessary and sufficient conditions for a linear estimator of a linear function of fixed and random effects in a balanced random model to be admissible are given. The formulae for admissible estimators depend on certain coefficients from the interval [0,1], as in well-known results for other models (see e.g. Cohen ).

2010 AMS Mathematics Subject Classification: Primary 62F10, 62C15; Secondary 62J10.

Keywords and phrases: balanced random models, linear estimation, linear prediction, admissibility among an affine set, locally best estimator.

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