Skip to contents

Register Seriation Methods from Package DendSer

Source: R/register_DendSer.R
register_DendSer.Rd

Register the DendSer dendrogram seriation method and the ARc criterion (Earle and Hurley, 2015) for use with seriate().

Usage

register_DendSer()

Value

Nothing.

Details

Registers the method "DendSer" for seriate. DendSer is a fast heuristic for reordering dendrograms developed by Earle and Hurley (2015) able to use different criteria.

control for seriate() with method "DendSer" accepts the following parameters:

  • "h" or "method": A dendrogram or a method for hierarchical clustering (see hclust). Default: complete-link.

  • "criterion": A seriation criterion to optimize (see list_criterion_methods("dist"). Default: "BAR" (Banded anti-Robinson from with 20% band width).

  • "verbose": a logical; print progress information?

  • "DendSer_args": additional arguments for DendSer::DendSer().

For convenience, the following methods (for different cost functions) are also provided:

  • "DendSer_ARc" (anti-robinson form),

  • "DendSer_BAR" (banded anti-Robinson form),

  • "DendSer_LPL" (lazy path length),

  • "DendSer_PL" (path length).

Note: Package DendSer needs to be installed.

References

D. Earle, C. B. Hurley (2015): Advances in dendrogram seriation for application to visualization. Journal of Computational and Graphical Statistics, 24(1), 1–25.

See also

DendSer::DendSer()

Other seriation: register_GA(), register_optics(), register_smacof(), register_tsne(), register_umap(), register_vegan(), registry_for_seriation_methods, seriate(), seriate_best()

Author

Michael Hahsler based on code by Catherine B. Hurley and Denise Earle

Examples


if (FALSE) { # \dontrun{
register_DendSer()
get_seriation_method("dist", "DendSer")

d <- dist(random.robinson(20, pre=TRUE))

## use Banded AR form with default clustering (complete-link)
o <- seriate(d, "DendSer_BAR")
pimage(d, o)

## use different hclust method (Ward) and AR as the cost function for
## dendrogram reordering
o <- seriate(d, "DendSer", control = list(method = "ward.D2", criterion = "AR"))
pimage(d, o)
} # }