MoE_Similarity function

Plot the Similarity Matrix of a MoEClust Mixture Model

Plot the Similarity Matrix of a MoEClust Mixture Model

Produces a heatmap of the similarity matrix constructed from the res$z matrix at convergence of a MoEClust mixture model.

MoE_Similarity(res, col = grDevices::heat.colors(30L, rev=TRUE), reorder = TRUE, legend = TRUE, ...)

Arguments

  • res: An object of class "MoEClust" generated by MoE_clust, or an object of class "MoECompare" generated by MoE_compare. Models with a noise component are facilitated here too.
  • col: A vector of colours as per image. Will be checked for validity.
  • reorder: A logical (defaults to TRUE) indicating whether observations should be reordered for visual clarity.
  • legend: A logical (defaults to TRUE) indicating whether to append a colour key legend.
  • ...: Catches unused arguments, or arguments to be passed to hclust when reorder=TRUE.

Returns

The similarity matrix in the form of a heatmap is plotted; the matrix itself can also be returned invisibly. The invisibly returned matrix will also be reordered if reordered=TRUE.

Note

plot.MoEClust is a wrapper to MoE_Similarity which accepts the default arguments, and also produces other types of plots.

Examples

data(ais) mod <- MoE_clust(ais[,3:7], G=2, modelNames="EEE", gating= ~ SSF + Ht, expert= ~ sex, network.data=ais, tau0=0.1, noise.gate=FALSE) sim <- MoE_Similarity(mod)

See Also

MoE_clust, plot.MoEClust,

Author(s)

Keefe Murphy - <keefe.murphy@mu.ie >

  • Maintainer: Keefe Murphy
  • License: GPL (>= 3)
  • Last published: 2025-03-05