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Higher Order Indicator with Rank-Related Clustering in Multi-indicator Systems

In: Multi-indicator Systems and Modelling in Partial Order

Author

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  • Wayne L. Myers

    (The Pennsylvania State University, Penn State Institutes of Energy and Environment)

  • Ganapati P. Patil

    (The Pennsylvania State University, Center for Statistical Ecology and Environmental Statistics, Department of Statistics)

Abstract

We extend exploration and application of a compound ranking regime for multi-indicator systems based on partial order theory that coordinates principal down-set, up-set, and comparability. We use this “balance of normalized definitive status (BONDS)” ranking in conjunction with augmented hierarchical clustering for comparing clusters as graded groups to obtain information relevant to number of clusters, group-wise ordering, and interaction of indicators. A case study is conducted with localities as instances (objects) and percentages for kinds of land cover as indicators. Hierarchical clustering is accomplished with the hclust facility of R software in conjunction with customized computational support in R.

Suggested Citation

  • Wayne L. Myers & Ganapati P. Patil, 2014. "Higher Order Indicator with Rank-Related Clustering in Multi-indicator Systems," Springer Books, in: Rainer Brüggemann & Lars Carlsen & Jochen Wittmann (ed.), Multi-indicator Systems and Modelling in Partial Order, edition 127, chapter 0, pages 331-341, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-8223-9_16
    DOI: 10.1007/978-1-4614-8223-9_16
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