| Curve {clues} | R Documentation |
A toy example used to illustrate curve clustering.
data(Curve)
A list contains a 300 by 10 data matrix (curve) and a 300 by 1 cluster membership vector (curve.mem). There are 3 clusters, each containing 100 data points, respectively, in a 10-dimensional space.
cluster one is generated from the model:
yik = sin(2 * PI * xk) + eik, xk ~ N(0, 1), eik ~ N(0, 0.1), i = 1, …, 100, k = 1, …, 10.
cluster two is generated from the model:
yik = cos(2 * PI * xk) + eik, xk ~ N(0, 1), eik ~ N(0, 0.1), i = 1, ..., 100, k = 1, ..., 10.
cluster three is generated from the model:
yik = eik, eik ~ N(0, 1), i = 1, ..., 100, k = 1, ..., 10.
data(Curve)
# data matrix
curve <- Curve$curve
# 'true' cluster membership
curve.mem <- Curve$curve.mem
# 'true' number of clusters
nClust <- length(unique(curve.mem))
# plot average trajectories
plotAvgCurves(curve, curve.mem)