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The quality of standards in Least Squares calibrations

机译:最小二乘校准中的标准质量

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摘要

Frequently, the Least Square Regression Model (LSRM) assumption related to standards quality is either forgotten or formulated in too strict of a way, making its application unsuccessful or difficult. This work posits that the LSRM requires calibration standards with concentration ratios affected by negligible uncertainties that are achievable for standard solutions with large relative uncertainties. Criterion to test this assumption and a model to take into account the uncertainty of standards in performed quantifications are presented. The developed models were successfully tested with a combination of experimental data about interpolation uncertainty, for the determination of hexachlorobenzene by GC-ECD, with simulated values of standards concentrations.
机译:通常,与标准质量有关的最小二乘回归模型(LSRM)假设被遗忘或制定得过于严格,从而使其应用不成功或困难。这项工作假设LSRM要求校准标准品的浓度比受可忽略不计的不确定度影响,而不确定度可用于具有较大相对不确定度的标准溶液。提出了检验该假设的标准以及考虑到执行量化中标准不确定性的模型。使用有关插值不确定性的实验数据,结合GC-ECD测定六氯苯和标准浓度的模拟值,成功开发了模型。

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