Abonnement à la biblothèque: Guest
Journal of Automation and Information Sciences

Publication de 12  numéros par an

ISSN Imprimer: 1064-2315

ISSN En ligne: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

Indexed in

Accuracy of Estimation of Parameters of Linear Regression on Errors in Variables

Volume 42, Numéro 11, 2010, pp. 18-30
DOI: 10.1615/JAutomatInfScien.v42.i11.20
Get accessGet access

RÉSUMÉ

We consider ultimate accuracy of estimation of parameters of linear regression under the presence of bounded errors of measurements of input variable and regressors on usage of several main nonstochastic estimation methods. It was shown that for sufficiently low level of errors of regressors the minimax approach makes it possible to obtain exact values of estimated parameters. For high level of these errors only polyhedron method with explicit consideration of regressors errors makes it possible to obtain exact values of parameters on realization of usual requirements to sequences of errors and input data without errors. The obtained results are illustrated by means of the numerical example.

CITÉ PAR
  1. Gubarev V. F., Salnikov N. N., Melnychuk S. V., Identification of Regularized Models in the Linear Regression Class, Cybernetics and Systems Analysis, 57, 4, 2021. Crossref

Portail numérique Bibliothèque numérique eBooks Revues Références et comptes rendus Collections Prix et politiques d'abonnement Begell House Contactez-nous Language English 中文 Русский Português German French Spain