Recombining observations in cluster analysis: the SAGRA method

This thesis wants to answer the question of how we can recombine this small homogeneous groups to reconstruct the structure of the data set

Recombining partitions from multivariate data: a clustering method on Bayes factors

We introduce SAGRA (Split And Group Recombining Algorithm), a cluster analysis methodology which split the data set into small homogeneous groups and later recombine those groups using Bayes factors.

Recombining partitions via unimodality tests

We develop an algorithm that integrates a splitting process inherited from the SAR algorithm (Peña et al., 2004) with unimodality tests such as the dip test proposed by Hartigan and Hartigan (1985), and finally, we use anetwork configuration to visualize the results

Recombining dependent data: an Order Statistics approach

This article discusses the problem of forming groups from previously split data.