deldupMclust: Delete duplicate found clusters
In edci: Edge Detection and Clustering in Images

Description Usage Arguments Details Value Author(s) References See Also

Delete clusters differing only by rounding errors or having maximization value zero.

1 2	deldupMclust(clust, prec = NULL, ncol = NULL, dz = TRUE)

`clust`	numerical matrix whose columns contain the parameters of the clusters.
`prec`	optional positive integer. Number of decimal places for rounding.
`ncol`	number of columns describing the clusters. See details.
`dz`	optional boolean. With `dz = TRUE`, those clusters for which the objective function has value 0 are deleted.

Since clusters found by oregMclust or circMclust often differ only by rounding errors, the function deldupMclust can be used for rounding and deleting duplicates. If clust has a column named "count", its values are summed appropriately. Otherwise such a column is added.

For parameter clust the object returned from oregMclust or circMclust can be used. Alternatively, an arbitrary matrix can be given, of which the first ncol columns describe the clusters. The parameter prec is the number of decimal places for rounding; the default is no rounding. With ncol, the number of columns that describe the clusters can be given. This is not needed, if clust is an object returned from oregMclust or circMclust.

An object of the same type as clust.

Tim Garlipp, TimGarlipp@gmx.de

Mueller, C. H., & Garlipp, T. (2005). Simple consistent cluster methods based on redescending M-estimators with an application to edge identification in images. Journal of Multivariate Analysis, 92(2), 359–385.

oregMclust, circMclust

edci documentation built on May 1, 2019, 7:44 p.m.