Calibration and measurement control based on Bayes statistics

K. Hangos, L. Leisztner, M. Karny

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The Bayesian methodology described in this paper has the inherent capability of choosing, from calibration-type curves, candidates which are plausible with respect to measured data, expert knowledge and theoretical models (including the nature of the measurement errors). The basic steps of Bayesian calibration are reviewed and possible applications of the results are described in this paper. A calibration related to head-space has chromatographic data is used as an example of the proposed method. The linear calibration case has been treated with a log-normal distributed measurement error. Such a treatment of noise stresses the importance of modelling the random constituents of any problem.

Original languageEnglish
Pages (from-to)149-155
Number of pages7
JournalJournal of Automatic Chemistry
Volume11
Issue number4
Publication statusPublished - 1989

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Calibration
Statistics
statistics
Measurement errors
methodology
curves
Noise
Theoretical Models
Head

ASJC Scopus subject areas

  • Clinical Biochemistry

Cite this

Calibration and measurement control based on Bayes statistics. / Hangos, K.; Leisztner, L.; Karny, M.

In: Journal of Automatic Chemistry, Vol. 11, No. 4, 1989, p. 149-155.

Research output: Contribution to journalArticle

Hangos, K. ; Leisztner, L. ; Karny, M. / Calibration and measurement control based on Bayes statistics. In: Journal of Automatic Chemistry. 1989 ; Vol. 11, No. 4. pp. 149-155.
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