Title: Consistent estimation in an implicit quadratic measurement error model
Authors: Kukush, A ×
Markovsky, Ivan
Van Huffel, Sabine #
Issue Date: Aug-2004
Publisher: Elsevier science bv
Series Title: Computational statistics & data analysis vol:47 issue:1 pages:123-147
Abstract: An adjusted least squares estimator is derived that yields a consistent estimate of the parameters of an implicit quadratic measurement error model. In addition, a consistent estimator for the measurement error noise variance is proposed. Important assumptions are: (1) all errors are uncorrelated identically distributed and (2) the error distribution is normal. The estimators for the quadratic measurement error model are used to estimate consistently conic sections and ellipsoids. Simulation examples, comparing the adjusted least squares estimator with the ordinary least squares method and the orthogonal regression method, are shown for the ellipsoid fitting problem. (C) 2003 Elsevier B.V. All rights reserved.
ISSN: 0167-9473
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Electrical Engineering - miscellaneous
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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