Model-mismatch errors in least-squares 1-D centering.

Details Model-mismatch errors in least-squares 1-D centering. Model-mismatch errors in least-squares 1-D centering.

May 1995

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995a%26as..111..183d&link_type=abstract

Astronomy and Astrophysics Supplement, v.111, p.183

Astronomy and Astrophysics

Astrophysics

9

Methods: Data Analysis, Methods: Numerical, Techniques: Spectroscopic

Scientific paper

The nature of "pixelation errors" in 1-D centering by means of least-squares fits is analyzed in detail. For the case of intrinsically symmetric data we propose an improved position estimator, based on a combination of the fit results obtained with an even and an odd number of fitpoints. Numerical tests on synthetic data confirm that the combined estimator reduces the pixelation errors - which might be called more aptly model mismatch errors - by roughly an order of magnitude. The influence of weak asymmetries in a feature is discussed and we indicate how, in practice, the importance of model mismatch errors (and the relevance of a correction thereof) with respect to noise-induced errors, can be assessed.

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