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Dealing with three-way data containing missing values by new weighted method for second-order calibration

文献类型： 外文期刊

作者： Li, Yong 1 ; Wu, Hai-long 3 ; Yu, Xiang-yang 1 ;

作者机构： 1.Jiangsu Acad Agr Sci, Inst Food Qual & Safety, 50 Zhongling St, Nanjing 210014, Jiangsu, Peoples R China

2.State Key Lab Breeding Base, Key Lab Food Qual & Safety Jiangsu Prov, 50 Zhongling Street;, Nanjing 210014, Jiangsu, Peoples R China

3.Hunan Univ, Coll Chem & Chem Engn, State Key Lab Chemo Biosensing & Chemometr, Changsha 410082, Hunan, Peoples R China

关键词： Weighted alternating penalty trilinear decomposition;Weighted PARAFAC;Incomplete data PARAFAC;Missing values;Second-order calibration

期刊名称：CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS （ 影响因子：3.491； 五年影响因子：3.839 ）

ISSN： 0169-7439

年卷期： 2017 年 171 卷

页码：

收录情况： SCI

摘要： Multi-way data arrays contain missing values for several reasons, such as various malfunctions of instruments, responses being outside instrument ranges, irregular measurement intervals between samples and data post processing. In the present study, one new method, weighted alternating penalty trilinear decomposition (W-APTLD), based on the weighted trilinear model and the idea of alternative trilinear decomposition was given to analyze three-way data arrays containing missing values. In addition, one improved core consistency diagnostic method (W-CORCONDIA) was proposed to estimate the chemical ranks of three-way data arrays containing missing values. The results of one simulation and two real data sets demonstrate that the new method W-APTLD could be used to deal with missing values and reserves the second-order advantage. When meeting excessive factors, W-APTLD could give more accurate results than weighted PARAFAC (W-PARAFAC), PARAFAC with single imputation (PARAFAC-SI) and incomplete data PARAFAC (INDAFAC). The convergence rate of W-APTLD was much faster than W-PARAFAC and PARAFAC-SI but slower than INDAFAC. Better than W-PARAFAC and PARAFAC-SI, W-APTLD could overcome the problem due to severe collinearity. In addition, this new method could be extended to analyze higher-way data arrays containing missing values.

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