A Distance Approach to Nonlinear Multivariate AnalysisMultivariate analysis and multidimensional scaling. Classification of MVA techniques: join and meet. STRIFE. STRAIN. STRESS. The majorization algorithm-model. Notation. Multivariate analysis via strife. The gifi system of nonlinear multivariate analysis. Join and meet. Homogeneity analysis. Principal components analysis. Classical principal components analysis. Nonlinear principal components analysis via join-STRIFE. Nonlinear principal components analysis via Meet-STRIFE. Canonical coordinates analysis. Classical canonical coordinates analysis. Nonlinear canonical coordinates analysis. Normalization. Multivariate analysis via strain. Distance properties of multivariate analysis. Join and meet. Principal components analysis. Canonical coordinates analysis. Homogeneity analysis. The asymmetric treatment of rows and columns. From classical to nonlinear multivariate analysis. Multivariate analysis via stress. From STRAIN to STRESS via multidimensional scaling. Multidimensional scaling with restrictions. Join and Meet. Homogeneity analysis. Principal components analysis. Classical principal components analysis. Nonlinear principal components analysis. Canonical coordinates analysis. Classical canonical coordinates analysis. Nonlinear canonical coordinates analysis. Cone regression with a non-diagonal weight matrix. Summary of the algorithm for nonlinear canonical coordinates analysis. Some special techniques in the stress framework. Simultaneous nonlinear principal components analysis with M sets. Asymmetric treatment of sets. Nonlinear redundancy analysis. Distance driven subspace approximation. Composite nonlinear principal components analysis. The majorization algorithm for multidimensional scaling. Overview of applications. Applications of multivariate analysis via strife. Homogeneity analysis of cetacea. Nonlinear principal components analysis of the United States. Nonlinear canonical coordinates analysis of the United States. Applications of multivariate analysis via strain. Principal coordinates analysis of city crime. Principal components analysis of city crime. Canonical coordinates analysis of the Southern States. Correspondence analysis and principal coordinates analysis of the parliament. Principal components analysis and classical MDS of criminal correlations. Applications of multivariate analysis via stress. Principal coordinates analysis of the parliament. Principal coordinates analysis of the parliament via constrained MDS. Homogeneity analysis of cetacea. Classical principal components analysis of city crime. Nonlinear principal components analysis of the United States. Classical canonical coordinates analysis of the Southern State. Nonlinear canonical coordinates analysis of the United States. Nonlinear redundancy analysis of the United States. Composite nonlinear principal components analysis of the United States. |
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algorithm applied approximation average axis canonical analysis canonical coordinates analysis centroid centroid principle Cetacea chi-square distances City Crime classical MDS computing convergence correlation matrix correspondence analysis data analysis data matrix Data Theory decomposition defined diagonal matrix dik(X dimensional space DOLPHIN eigenanalysis eigenvalues Euclidean distances Figure framework Gifi system given in Table Guttman transform high-dimensional space HOMIC homogeneity analysis ILLIT Join-loss Kruskal Leiden loss function loss of homogeneity low-dimensional space Mahalanobis distances Meet-loss Meet-STRAIN Meet-techniques metric projection Meulman minimized minimum loss monotone transformations multidimensional scaling multivariate analysis MVA techniques nonlinear canonical coordinates nonlinear MVA nonlinear principal components nonmetric normalization objects obtained original p-dimensional parties points principal components analysis principal coordinates analysis problem proper loss Psychometrika PvdA Pythagorean distances redundancy analysis residuals result rows scalar product scalar product matrix scores solution STRESS(X STRIFE subspace transformed variables vector Whales