A framework for sequential multiblock component methods

Journal of Chemometrics - Tập 17 Số 6 - Trang 323-337 - 2003
Age K. Smilde1,2, Johan A. Westerhuis1, S. De Jong3
1Process Analysis and Chemometrics, Department of Chemical Engineering, University of Amsterdam, Nieuwe Achtergracht 166, NL-1018 WV Amsterdam, The Netherlands
2TNO Nutrition and Food Research, Utrechtseweg 48, NL-3700 AJ Zeist, The Netherlands
3Unilever Research and Development Vlaardingen, PO Box 114, NL-3130 AC Vlaardingen, The Netherlands

Tóm tắt

AbstractMultiblock or multiset methods are starting to be used in chemistry and biology to study complex data sets. In chemometrics, sequential multiblock methods are popular; that is, methods that calculate one component at a time and use deflation for finding the next component. In this paper a framework is provided for sequential multiblock methods, including hierarchical PCA (HPCA; two versions), consensus PCA (CPCA; two versions) and generalized PCA (GPCA). Properties of the methods are derived and characteristics of the methods are discussed. All this is illustrated with a real five‐block example from chromatography. The only methods with clear optimization criteria are GPCA and one version of CPCA. Of these, GPCA is shown to give inferior results compared with CPCA. Copyright © 2003 John Wiley & Sons, Ltd.

Từ khóa


Tài liệu tham khảo

Coppi R, 1989, Multiway Data Analysis

Law HG, 1984, Research Methods for Multimode Data Analysis

10.1007/BF02294207

10.1002/1099-128X(200005/06)14:3<301::AID-CEM594>3.0.CO;2-H

10.1093/biomet/58.3.433

10.1007/BF02289472

10.1007/BF02294629

10.1111/j.2044-8317.1994.tb01027.x

NieropAFM.Multidimensional analysis of grouped variables: an integrated approach.PhD Thesis University of Leiden 1993.

Ten Berge JMF, 1992, Simultaneous component analysis, Statist. Appl., 4, 277

TimmermanME.Component analysis of multisubject multivariate longitudinal data.PhD Thesis University of Groningen 2001.

10.1016/S0167-9473(00)00024-4

10.1016/S0003-2670(00)84409-8

10.1002/cem.1180030104

WoldS HellbergS LundstedtT SjostromM WoldH.PLS modeling with latent variables in two or more dimensions.Proceedings PLS‐meeting Frankfurt Germany 1987;1–21.

10.1002/(SICI)1099-128X(199609)10:5/6<463::AID-CEM445>3.0.CO;2-L

10.1002/cem.667

10.1002/(SICI)1099-128X(199809/10)12:5<301::AID-CEM515>3.0.CO;2-S

10.1016/0959-1524(95)00019-M

10.1016/S0169-7439(98)00024-0

10.1007/BF02291478

10.1007/BF02294132

10.1021/ac00063a019

10.1002/cem.1180090105

10.1016/S0169-7439(98)00162-2

Geladi P, 1988, Multivariate comparison of laboratory measurements, Symp. on Applied Statistics, 15

10.1002/cem.1180020306

10.1016/S0021-9673(98)00749-3

10.1007/BF02268461

Engelhardt H, 1997, A chromatographic test procedure for reversed‐phase HPLC column evaluation, LC GC Int., 803

Claessens HA, 2003, Multiple column tests for reversed‐phase liquid chromatographic columns. Part 1: A comparative chromatographic study, J. Chromatogr.

Schoenmakers PJ, 1986, Optimization of Chromatographic Selectivity

Atkinson AC, 1985, Plots, Transformations, and Regression: An Introduction to Graphical Methods of Diagnostic Regression Analysis

10.1007/BF02306029

10.2307/2347233

Yanai H, 1974, Unification of various techniques of multivariate analysis by means of generalized coefficient of determination (GCD), J. Behaviormetrics, 1, 45