摘要
用检测器阵列进行多组分定量分析时,体系常不同程度地受复共线关系的影响,致使多种基于最小二乘原理的校正方法难于获得稳定的预测结果.为此,本文在文献的基础上,提出了对每一组分分别建立预测模型的LRE(latent Root Estimator)方法.5组分药物体系的定量分析表明本法具有良好的实用性,其浓度预测结果优于最小二乘及主成分估计.
In this paper a new method for achieving predictive models, called latent root estimator, is introduced. The technique was utilized for the simultaneously quantitative measurement of a system containing five components (salicylic acid, thymol, phenol, benzoic acid and resorcin) from their severely overlapping UV spectra and the predictive performance of the resultant calibration model was tested with a separate set of samples. The results indicate that the method possesses an obvious significance to gain stable predictive equations for collinearity systems and to reduce the influence of instrumental noise for concentration estimation.
出处
《高等学校化学学报》
SCIE
EI
CAS
CSCD
北大核心
1992年第4期464-466,共3页
Chemical Journal of Chinese Universities
基金
国家自然科学基金
国家教委博士学位点基金
关键词
校正技术
特征根估计
分光光度法
Calibration technique, Latent root estimator, Spectrophotometry
