On admissibility of linear estimators in models with finitely generated parameter space

Ewa Synówka-Bejenka; Stefan Zontek

Kybernetika (2016)

  • Volume: 52, Issue: 5, page 724-734
  • ISSN: 0023-5954

Abstract

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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.

How to cite

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Synówka-Bejenka, Ewa, and Zontek, Stefan. "On admissibility of linear estimators in models with finitely generated parameter space." Kybernetika 52.5 (2016): 724-734. <http://eudml.org/doc/287568>.

@article{Synówka2016,
abstract = {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.},
author = {Synówka-Bejenka, Ewa, Zontek, Stefan},
journal = {Kybernetika},
keywords = {linear model; linear estimation; linear prediction; admissibility; admissibility among an affine set; locally best estimator; linear model; linear estimation; linear prediction; admissibility; admissibility among an affine set; locally best estimator},
language = {eng},
number = {5},
pages = {724-734},
publisher = {Institute of Information Theory and Automation AS CR},
title = {On admissibility of linear estimators in models with finitely generated parameter space},
url = {http://eudml.org/doc/287568},
volume = {52},
year = {2016},
}

TY - JOUR
AU - Synówka-Bejenka, Ewa
AU - Zontek, Stefan
TI - On admissibility of linear estimators in models with finitely generated parameter space
JO - Kybernetika
PY - 2016
PB - Institute of Information Theory and Automation AS CR
VL - 52
IS - 5
SP - 724
EP - 734
AB - 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.
LA - eng
KW - linear model; linear estimation; linear prediction; admissibility; admissibility among an affine set; locally best estimator; linear model; linear estimation; linear prediction; admissibility; admissibility among an affine set; locally best estimator
UR - http://eudml.org/doc/287568
ER -

References

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