Robust surrogate measurement correction using generalised additive model

Karl Ropkins; Hu Li; Gary Hawley; Haibo Chen; James Tate; Gordon Andrews; Margaret Bell

doi:10.1016/j.chemolab.2008.10.005

Robust surrogate measurement correction using generalised additive model

Karl Ropkins, Hu Li, Gary Hawley, Haibo Chen, James Tate, Gordon Andrews, Margaret Bell

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	164-169
Journal	Chemometrics and Intelligent Laboratory Systems
Volume	95
Issue number	2
DOIs	https://doi.org/10.1016/j.chemolab.2008.10.005
Publication status	Published - 2009

Keywords

Generalised additive model (GAM)
Vehicle exhaust flow
Measurement correction
Pitot exhaust flow meter

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10.1016/j.chemolab.2008.10.005

Cite this

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title = "Robust surrogate measurement correction using generalised additive model",

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.",

keywords = "Generalised additive model (GAM), Vehicle exhaust flow, Measurement correction, Pitot exhaust flow meter",

author = "Karl Ropkins and Hu Li and Gary Hawley and Haibo Chen and James Tate and Gordon Andrews and Margaret Bell",

year = "2009",

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T1 - Robust surrogate measurement correction using generalised additive model

AU - Ropkins, Karl

AU - Li, Hu

AU - Hawley, Gary

AU - Chen, Haibo

AU - Tate, James

AU - Andrews, Gordon

AU - Bell, Margaret

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Generalised additive model (GAM)

KW - Vehicle exhaust flow

KW - Measurement correction

KW - Pitot exhaust flow meter

UR - https://www.scopus.com/pages/publications/58149204180

UR - http://dx.doi.org/10.1016/j.chemolab.2008.10.005

U2 - 10.1016/j.chemolab.2008.10.005

DO - 10.1016/j.chemolab.2008.10.005

M3 - Article

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SP - 164

EP - 169

JO - Chemometrics and Intelligent Laboratory Systems

JF - Chemometrics and Intelligent Laboratory Systems

IS - 2

ER -

Robust surrogate measurement correction using generalised additive model

Abstract

Keywords

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