Quotation Rusch, Thomas, Mair, Patrick, Hornik, Kurt. 2021. Cluster Optimized Proximity Scaling. Journal of Computational and Graphical Statistics. 30 (4), 1156-1167.




Proximity scaling methods such as Multidimensional Scaling (MDS) represent objects in a low dimensional configuration so that fitted object distances optimally approximate object proximities. Besides finding the optimal configuration, an additional goal may be to make statements about the cluster arrangement of objects. This fails if the configuration lacks appreciable clusteredness. We present Cluster Optimized Proximity Scaling (COPS), which attempts to find a configuration that exhibits clusteredness. In COPS, a flexible parametrized scaling loss function that may emphasize differentiation information in the proximities is augmented with an index (OPTICS Cordillera) that penalizes lack of clusteredness of the configuration. We present two variants of this, one for finding a configuration directly and one for hyperparameter selection for parametric stresses. We apply both to a functional magnetic resonance imaging (fMRI) data set on neural representations of mental states in a social cognition task and show that COPS improves clusteredness of the configuration, enabling visual identification of clusters of mental states. Online supplementary material is available including an R package and a document with additional details.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Computational and Graphical Statistics
Citation Index SCI
WU-Journal-Rating new FIN-A, VW-C
Language English
Title Cluster Optimized Proximity Scaling
Volume 30
Number 4
Year 2021
Page from 1156
Page to 1167
Reviewed? Y
URL https://www.tandfonline.com/doi/full/10.1080/10618600.2020.1869027?src=
DOI https://doi.org/10.1080/10618600.2020.1869027
Open Access Y
Open Access Link https://www.tandfonline.com/doi/full/10.1080/10618600.2020.1869027?src=


Rusch, Thomas (Details)
Mair, Patrick (Former researcher)
Hornik, Kurt (Details)
Competence Center for Empirical Research Methods WE (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1162 Statistics (Details)
5509 Psychological methodology (Details)
5701 Applied statistics (Details)
5704 Social statistics (Details)
5912 Social sciences (interdisciplinary) (Details)
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