A novel method to estimate the chemical rank of three-way data for second-order calibration

详细信息    查看全文

• 作者：Yong Li ; Hai-Long Wu ; Xiang-Dong Qing ; Qi Zuo ; Yao Chen ; Ru-Qin Yu
• 关键词：Self-weighted alternating trilinear decomposition with Monte Carlo simulation (SWATLD-MCS) ; ADD-ONE-UP ; CORCONDIA ; SWATLD ; Second-order calibration
• 刊名：Chemometrics and Intelligent Laboratory Systems
• 出版年：2013
• 出版时间：15 August, 2013
• 年：2013
• 卷：127
• 期：Complete
• 页码：177-184
• 全文大小：1034 K

文摘

A novel method, self-weighted alternating trilinear decomposition with Monte Carlo simulation (SWATLD-MCS), is developed to determine the chemical rank of three-way data for second-order calibration. The proposed method estimates the chemical rank by comparing the values of sorted mean relative-concentration (SMRC), which are obtained from SWATLD by decomposing one pseudo three-way data array created by Monte Carlo simulation. The results for two simulated and two real three-way data sets are presented, in comparison with other two factor-determining methods, i.e., ADD-ONE-UP and the core consistency diagnostic (CORCONDIA). These results demonstrate that this new method can accurately estimate chemical ranks of complex systems even when heavy collinearity and high-intensity noise are present. Also the method has a lower computational burden than competitive methods, which saves overall analysis time. In addition, this new methodology can be extended to: i) other second-order calibration algorithms, being insensitive to excessive factors, can be used with this method; ii) the chemical rank of higher-order data can be determined by this method, using higher-order calibration algorithms.