Abstract:
clv clusters variables around latent components. The variables are clustered by searching to minimize at each step the decreasing of the T criterion computed as the sum of the first eigenvalues of the matrices of data of all the clusters. A hierarchical cluster analysis based on this criterion is realized. A consolidation procedure can be run in a second time, which allows assigning each variable to the more correlated latent components. The procedure is described by Vigneau and Qannari (Communications in Statistics - Simulation and Computation, 2003).
Language: Stata Requires: Stata version 8.0 Keywords:Clustering around latent components; Varclus; CLV; unidimensionality (search for similar items in EconPapers) Date: 2005-06-12, Revised 2006-10-14 Note: This module may be installed from within Stata by typing "ssc install clv". Windows users should not attempt to download these files with a web browser.
More software in Statistical Software Components from Boston College Department of Economics Address: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA Contact information at EDIRC. Series data maintained by Christopher F Baum ().
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