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A particular factor analysis model with parameter constraints is generalized to include classification problems definable within a framework of fitting linear models. The sequential fitting (SEFIT) approach of principal component analysis is extended to include several nonstandard data analysis...
We consider two or more ultrametric distance matrices defined over different, possibly overlapping, subsets. These matrices are merged into one ultrametric matrix defined over the whole set. Necessary and sufficient conditions for uniqueness of the merging are established. when these conditions...
ConsiderN entities to be classified, with given weights, and a matrix of dissimilarities between pairs of them. The split of a cluster is the smallest dissimilarity between an entity in that cluster and an entity outside it. The single-linkage algorithm provides partitions intoM clusters for...
This note introduces the coefficient of variation biplot, and suggests that it will provide a useful graphical display of data matrices in which the relative variability of the columns is of interest.
The paper addresses the problem of specifying differential weights for variables in the construction of a measure of dissimilarity. An assessor is required to provide subjective judgments of the pairwise dissimilarities within a training set of objects, and these dissimilarities are then modeled...
Recently, algorithms for optimally weighting variables in non-hierarchical and hierarchical clustering methods have been proposed. Preliminary Monte Carlo research has shown that at least one of these algorithms cross-validates extremely well.
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