Nonlinear calibration transfer based on hierarchical Bayesian models and Lagrange Multipliers: Error bounds of estimates via Monte Carlo - Markov Chain sampling

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• 作者：Felicia Seichter^a ; Josef Vogt^b ; ^{josef.vogt@uni-ulm.de} ; Peter Radermacher^b ; Boris Mizaikoff^a ; ^{boris.mizaikoff@uni-ulm.de} ;
• 关键词：Calibration transfer ; Lagrange Multipliers ; Fluorescence ; Hierarchical models ; Oxygen sensor ; Bayesian statistics
• 刊名：Analytica Chimica Acta
• 出版年：2017
• 出版时间：25 January 2017
• 年：2017
• 卷：951
• 期：Complete
• 页码：32-45
• 全文大小：1672 K
• 卷排序：951

文摘

The inter-occasional distribution of coefficients for a nonlinear calibration curve is assessed. Coefficients of an actual calibration curve are a sample of the inter-occasional distribution. This sample and few actual measurements are sufficient to assess an actual calibration curve. A new calibration transfer method is proposed using minimal calibration effort. The model is confirmed by random subset cross validation for the calibration of an oxygen sensor.