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An Explicit Characterization of Admissible Linear Estimators of Fixed and Random Effects in Balanced Random Models

Synówka-Bejenka Ewa, Zontek Stefan

Probability and Mathematical Statistics

2020

Vol. 40, Fasc. 1

105--118

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 [3]).

On admissible quadratic estimation in a special linear model

Neumann K.

Probability and Mathematical Statistics

2005

Vol. 25, Fasc. 2

257--265

A random linear model for spatially located sensors measured intensity of a source of signals in discrete instants of time is considered. A characterization of admissible quadratic estimators of the mean squared error of a linear estimator of the expectation of the intensity is given.