Binary trees for dissimilarity data

Raffaella Piccarreta

Computational Statistics & Data Analysis, 2010, vol. 54, issue 6, 1516-1524

Abstract: Binary segmentation procedures (in particular, classification and regression trees) are extended to study the relation between dissimilarity data and a set of explanatory variables. The proposed split criterion is very flexible, and can be applied to a wide range of data (e.g., mixed types of multiple responses, longitudinal data, sequence data). Also, it can be shown to be an extension of well-established criteria introduced in the literature on binary trees.

Keywords: Dissimilarity; matrix; Classification; and; regression; trees; Binary; segmentation; Multivariate; responses; Perception; data; Ecological; data (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (4)

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