Comparison of principal analysis and the Tucker3 model

Helena Morais, Christina Ramos, Esther Forgács, Annamaria Jakab, Tibor Cserháti, José Oliviera, Tibor Illés, Zoltán Illés

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5 Citations (Scopus)


A three-ways array data matrix consisting of the activity data of laccase enzyme has been evaluated by both principal component analyses (PCA) and Tucker3 model. Activity data have been determined in 28 culture media, at 6 sampling times and by four strains of Lentinus edodes. PCA has been carried out three times one of the factors being always the variables and the other two factors being the observations. The dimensionality of the matrices of loadings calculated by PCAs and those of component matrices of Tucker3 model has been reduced to two by the nonlinear mapping technique. It has been found that the dimensionality of component matrices for Tucker3 model can be predicted from the results of PCAs. Linear regression analyses indicated that the distribution of the original data points on the two-dimensional nonlinear maps considerably depends on the fact that the data have been calculated by PCA or by Tucker3 model.
Original languageEnglish
Pages (from-to)449-455
Number of pages7
JournalQSAR and Combinatorial Science
Issue number4
Publication statusPublished - 31 May 2003


  • laccase activity
  • PCA
  • Tucker3 model
  • nonlinear mapping


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