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Weighing schemes in multivariate data analysis
Author(s) -
Höskuldsson Agnar
Publication year - 2001
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.672
Subject(s) - interpretability , computer science , relation (database) , task (project management) , simple (philosophy) , multivariate statistics , data mining , focus (optics) , interpretation (philosophy) , quality (philosophy) , scheme (mathematics) , machine learning , artificial intelligence , mathematics , philosophy , physics , management , epistemology , programming language , optics , economics , mathematical analysis
A collection of methods will be presented, designed to reflect special purpose or features in data. Many chemometric methods can be viewed as an application of special weighing schemes of the type presented here. After a short review of the H‐principle of mathematical modelling, it will be applied to develop different weighing schemes and some simple ways to judge the quality or significance of a weighing scheme. Weighing schemes for two‐way data will be established. We shall show how a loading vector can be adapted to a given score vector in order to improve the possibilities of interpretation of the results. These results will be extended to multiway data. It will be shown how we can develop different weighing schemes for multiway data depending on the purpose or interpretability of the results. The importance of these weighing schemes is due to the fact that they yield or emphasize the part of data that is ‘in focus’ in relation to the task in question. Copyright © 2001 John Wiley & Sons, Ltd.