Output details
15 - General Engineering
University of Surrey
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Article title
Bayesian linear regression and variable selection for spectroscopic calibration
Type
D - Journal article
Title of journal
Analytica Chimica Acta
Article number
-
Volume number
631
Issue number
1
First page of article
13
ISSN of journal
00032670
Year of publication
2009
URL
-
Number of additional authors
-
Additional information
This article is among the first to apply the Bayesian approach to multivariate chemometric calibration of spectroscopy. Methodologically it demonstrates that the ridge regression, well-known in the chemometric community, is a special case of Bayesian linear regression; subsequently a Bayesian variable selection approach is proposed that substantially improves the calibration accuracy. This work has seen significant follow-up in the literature.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-