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Robust surrogate measurement correction using generalised additive model

Lookup NU author(s): Professor Margaret Carol Bell CBE

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Abstract

The generalised additive model (GAM) was developed as a prognostic tool for the investigation of data set trends. However, it is also proposed as a viable framework for the development of surrogate measurement corrections for instrumental data sets. This hypothesis is supported by an example application, the development of a robust vehicle exhaust flow measurement correction for a flow meter with a known measurement error.


Publication metadata

Author(s): Ropkins K, Li H, Hawley G, Chen H, Tate JE, Andrews G, Bell MC

Publication type: Article

Publication status: Published

Journal: Chemometrics and Intelligent Laboratory Systems

Year: 2008

Volume: 95

Issue: 2

Pages: 164-169

ISSN (print): 0169-7439

ISSN (electronic): 1873-3239

URL: http://dx.doi.org/10.1016/j.chemolab.2008.10.005

DOI: 10.1016/j.chemolab.2008.10.005


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