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Uncertainty in rate constants estimated from spectral data with baseline drift
Author(s) -
Furusjö Erik,
Danielsson LarsGöran
Publication year - 2000
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/1099-128x(200009/12)14:5/6<483::aid-cem620>3.0.co;2-j
Subject(s) - bootstrapping (finance) , subspace topology , noise (video) , baseline (sea) , projection (relational algebra) , statistics , least squares function approximation , constant (computer programming) , mathematics , algorithm , computer science , econometrics , artificial intelligence , mathematical analysis , image (mathematics) , programming language , geology , oceanography , estimator
This paper concerns the impact of baseline drift and noise on some methods for rate constant estimation from spectroscopic reaction monitoring data, and means to assess the uncertainty in the estimates. The methods studied are a target testing procedure and non‐linear least squares fitting. Both simulated and experimental data are used. The experimental data are from in situ UV/VIS and in situ ATR mid‐IR monitoring of ester hydrolysis reactions. For non‐linear least squares fitting, biased estimates are obtained when baseline drift is present, since the drift violates the model assumptions. The target testing procedure, on the other hand, can be used to reliably determine rate constants from spectroscopic data with baseline drift. Owing to the use of a projection onto a stochastic subspace, bias can occur in the estimated rate constants also for this method. However, the results indicate that in most cases this bias is not significant in practice. Bias and precision in the estimated rate constants are dependent on noise level and overlap in the spectral and time domains of the data. Bootstrapping can be used to calculate confidence intervals that have good coverage properties in most cases. Copyright © 2000 John Wiley & Sons, Ltd.