Nothing
## ---- message=FALSE, warning=FALSE-------------------------------------------
library(OptCirClust)
X = rgamma(70, 6)
K = 7
frame.size = 50
## ---- message=FALSE, warning=FALSE-------------------------------------------
# Our recommended method is the fast and optimal linear.polylog:
result_linear.polylog <- FramedClust(X, K, frame.size, method = "linear.polylog")
# The slow and optimal via repeatedly calling Ckmeans.1d.dp:
result_Ckmeans.1d.dp <- FramedClust(X, K, frame.size, method = "Ckmeans.1d.dp")
# The slow and heuristic via repeatedly calling kmeans:
result_kmeans <- FramedClust(X, K, frame.size, method = "kmeans")
## ---- message=FALSE, warning=FALSE, fig.width = 5, fig.asp = .92-------------
plot(result_linear.polylog, main = "linear.polylog: optimal\n***Recommended***")
plot(result_Ckmeans.1d.dp, main = "Repeated Ckmeans.1d.dp: quadratic time\nalways optimal")
plot(result_kmeans, main = "Repeated kmeans: heuristic\nnot always optimal")
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