The paper refers to the research on the characterization of admissible estimators initiated by Cohen \cite{Cohen}. In our paper it is proved that for linear models with finitely generated parameter space the limit of a sequence of the unique locally best linear estimators is admissible. This result is used to give a characterization of admissible linear estimators of fixed and random effects in a random linear model for spatially located sensors measuring intensity of a source of signals in discrete instants of time.
admissibility, linear model, linear estimation, linear prediction, admissibility among an affine set, locally best estimator
62F10, 62J10