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On admissibility of linear estimators in models with finitely generated parameter space
Kybernetika, Tome 52 (2016) no. 5, pp. 724-734 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The paper refers to the research on the characterization of admissible estimators initiated by Cohen [2]. 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.
The paper refers to the research on the characterization of admissible estimators initiated by Cohen [2]. 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.
DOI : 10.14736/kyb-2016-5-0724
Classification : 62F10, 62J10
Keywords: linear model; linear estimation; linear prediction; admissibility; admissibility among an affine set; locally best estimator 
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Synówka-Bejenka, Ewa; Zontek, Stefan. On admissibility of linear estimators in models with finitely generated parameter space. Kybernetika, Tome 52 (2016) no. 5, pp. 724-734. doi: 10.14736/kyb-2016-5-0724

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