plot.net_clustering: Plot Sequence Clustering Results

In Nestimate: Network Estimation, Bootstrap, and Higher-Order Analysis

Plot Sequence Clustering Results

Description

Plot Sequence Clustering Results

Usage

## S3 method for class 'net_clustering'
plot(
  x,
  type = c("silhouette", "mds", "heatmap", "predictors"),
  combined = TRUE,
  ...
)

Arguments

x	A net_clustering object.
type	Character. Plot type: "silhouette" (per-observation silhouette bars), "mds" (2D MDS projection), or "heatmap" (distance matrix heatmap ordered by cluster). Default: "silhouette".
combined	Logical. For type = "predictors" only: when TRUE (default), covariate forest panels are combined into a single faceted plot; when FALSE, a list of separate ggplots is returned.
...	Unsupported. Supplying unused arguments raises an error.

Value

A ggplot object (invisibly).

Examples

seqs <- data.frame(V1 = c("A","B","C","A","B"), V2 = c("B","C","A","B","A"),
                   V3 = c("C","A","B","C","B"))
cl <- build_clusters(seqs, k = 2)
plot(cl, type = "silhouette")

set.seed(1)
seqs <- data.frame(
  V1 = sample(c("A","B","C"), 20, TRUE),
  V2 = sample(c("A","B","C"), 20, TRUE),
  V3 = sample(c("A","B","C"), 20, TRUE)
)
cl <- build_clusters(seqs, k = 2)
plot(cl, type = "silhouette")

Nestimate documentation built on July 11, 2026, 1:09 a.m.