1985
DOI: 10.1016/s0003-2670(00)84410-4
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A software package for the evaluation of peak parameters in an analytical signal based on a non-linear regression method

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Cited by 24 publications
(5 citation statements)
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“…Third, we affirm our acquisition rates were sufficient to predict N . The Nyquist theorem ensures fidelity of a Gaussian if seven points are acquired, , although studies on area determination recommend the acquisition of 10 or more points/standard deviation. To preserve fidelity, the acquisition rate also should increase with decreasing S/N. These findings are only partly relevant, however, since our peaks are not Gaussians and we are concerned with N .…”
Section: Resultsmentioning
confidence: 99%
“…Third, we affirm our acquisition rates were sufficient to predict N . The Nyquist theorem ensures fidelity of a Gaussian if seven points are acquired, , although studies on area determination recommend the acquisition of 10 or more points/standard deviation. To preserve fidelity, the acquisition rate also should increase with decreasing S/N. These findings are only partly relevant, however, since our peaks are not Gaussians and we are concerned with N .…”
Section: Resultsmentioning
confidence: 99%
“…The data processing included correction for linear drift of the (digitized) detector signal and, in the case of correlation experiments, cross-correlation between the detector signal and a pattern close related to the injection pattern. 44 To determine the peak parameters, a peak-fitting procedure was applied to the correlogram or the electropherogram, using a nonlinear regression software package with a Fraser-Suzuki peak model 46 and a second-order polynomial describing the baseline. Noise levels, expressed as standard deviations, were calculated from the main baseline part of the correlogram or electropherogram.…”
Section: Methodsmentioning
confidence: 99%
“…To determine the peak parameters, a peak-fitting procedure was applied to the correlogram or the electropherogram, using a nonlinear regression software package with a Fraser−Suzuki peak model and a second-order polynomial describing the baseline. Noise levels, expressed as standard deviations, were calculated from the main baseline part of the correlogram or electropherogram.…”
Section: Methodsmentioning
confidence: 99%
“…The required fitting flexibility was obtained by exponentially modifying a tailing peak model, i.e. the Fraser-Suzuki function (21). Profiles from rat samples were analyzed for insulin and PI; in subsequent analysis, peaks of insulin I and II and of PI I and II were counted separately and/or in combination.…”
Section: Calculationsmentioning
confidence: 99%