GVME_Consensus: Gordon-Vichi Macroeconomic Consensus Partition Data

Description Usage Format Details Source References Examples

Description

The soft (“fuzzy”) consensus partitions for the macroeconomic partition data given in Gordon and Vichi (2001).

Usage

1
data("GVME_Consensus")

Format

A named cluster ensemble of eight soft partitions of 21 countries terms into two or three classes.

Details

The elements of the ensemble are consensus partitions for the macroeconomic partition data in Gordon and Vichi (2001), which are available as data set GVME. Element names are of the form "m/k", where m indicates the consensus method employed (one of MF1, MF2, JMF, and S&S, corresponding to the application of models 1, 2, and 3 in Gordon and Vichi (2001) and the approach in Sato and Sato (1994), respectively), and k denotes the number classes (2 or 3).

Source

Tables 4 and 5 in Gordon and Vichi (2001).

References

A. D. Gordon and M. Vichi (2001). Fuzzy partition models for fitting a set of partitions. Psychometrika, 66, 229–248. doi: 10.1007/BF02294837.

M. Sato and Y. Sato (1994). On a multicriteria fuzzy clustering method for 3-way data. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2, 127–142.
doi: 10.1142/S0218488594000122.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
## Load the consensus partitions.
data("GVME_Consensus")
## Pick the partitions into 2 classes.
GVME_Consensus_2 <- GVME_Consensus[1 : 4]
## Fuzziness using the Partition Coefficient.
cl_fuzziness(GVME_Consensus_2)
## (Corresponds to 1 - F in the source.)
## Dissimilarities:
cl_dissimilarity(GVME_Consensus_2)
cl_dissimilarity(GVME_Consensus_2, method = "comem")


Search within the clue package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.