A number of methods for the analysis of three-way data are described and shown to be variants of principal components analysis (PCA) of the two-way supermatrix in which each two-way slice is "strung out" into a column vector. The methods are shown to form a hierarchy such that each method is a constrained variant of its predecessor. A strategy is suggested to determine which of the methods yields the most useful description of a given three-way data set.</p
Multilinear analysis methods such as component (and three-way component) analysis of very large data...
This paper is concerned with methods of three-way two-mode multi- dimensional scaling which were dev...
Three-way Tucker analysis and CANDECOMP/PARAFAC are popular methods for the analysis of three-way da...
A number of methods for the analysis of three-way data are described and shown to be variants of pri...
Three-way component analysis techniques are designed for descriptive analysis of 3-way data, for exa...
Three-way component analysis techniques are designed for descriptive analysis of 3-way data, for exa...
A problem often occurring in exploratory data analysis is how to summarize large numbers of variable...
Hierarchical classes (HICLAS) models for multi-way multi-mode data constitute a unique family of cla...
Hierarchical classes (HICLAS) models for multi-way multi-mode data constitute a unique family of cla...
Three-way methods are multivariate data analysis tools that compress and visualize simultaneous vari...
In Chapter 1 we presented several denitions and concepts whose comprehension was crucial to fully un...
Three-way methods are multivariate data analysis tools that compress and visualize simultaneous vari...
Vertices Principal Component Analysis (V-PCA) and Centers Principal Component Analysis (C-PCA) are v...
Other publications in this series: Jacqueline Meulman, Homogeneity analysis of incomplete data. M &a...
Multilinear analysis methods such as component (and three-way component) analysis of very large data...
This paper is concerned with methods of three-way two-mode multi- dimensional scaling which were dev...
Three-way Tucker analysis and CANDECOMP/PARAFAC are popular methods for the analysis of three-way da...
A number of methods for the analysis of three-way data are described and shown to be variants of pri...
Three-way component analysis techniques are designed for descriptive analysis of 3-way data, for exa...
Three-way component analysis techniques are designed for descriptive analysis of 3-way data, for exa...
A problem often occurring in exploratory data analysis is how to summarize large numbers of variable...
Hierarchical classes (HICLAS) models for multi-way multi-mode data constitute a unique family of cla...
Hierarchical classes (HICLAS) models for multi-way multi-mode data constitute a unique family of cla...
Three-way methods are multivariate data analysis tools that compress and visualize simultaneous vari...
In Chapter 1 we presented several denitions and concepts whose comprehension was crucial to fully un...
Three-way methods are multivariate data analysis tools that compress and visualize simultaneous vari...
Vertices Principal Component Analysis (V-PCA) and Centers Principal Component Analysis (C-PCA) are v...
Other publications in this series: Jacqueline Meulman, Homogeneity analysis of incomplete data. M &a...
Multilinear analysis methods such as component (and three-way component) analysis of very large data...
This paper is concerned with methods of three-way two-mode multi- dimensional scaling which were dev...
Three-way Tucker analysis and CANDECOMP/PARAFAC are popular methods for the analysis of three-way da...