This function massages the input quaternion time series to feed them into the k-means alignment algorithm for jointly clustering and aligning the input QTS.
Usage
kmeans(x, k, iter_max = 10, nstart = 1, ...)
# S3 method for default
kmeans(
x,
k,
iter_max = 10,
nstart = 1,
algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"),
trace = FALSE,
...
)
# S3 method for qts_sample
kmeans(
x,
k = 1,
iter_max = 10,
nstart = 1,
centroid = "mean",
dissimilarity = "l2",
warping = "affine",
...
)
Arguments
- x
Either a numeric matrix of data, or an object that can be coerced to such a matrix (such as a numeric vector or a data frame with all numeric columns) or an object of class qts_sample.
- k
An integer value specifying the number of clusters to be look for.
- iter_max
An integer value specifying the maximum number of iterations for terminating the k-mean algorithm. Defaults to
10L
.- nstart
An integer value specifying the number of random restarts of the algorithm. The higher
nstart
, the more robust the result. Defaults to1L
.- ...
not used.
- algorithm
character: may be abbreviated. Note that
"Lloyd"
and"Forgy"
are alternative names for one algorithm.- trace
logical or integer number, currently only used in the default method (
"Hartigan-Wong"
): if positive (or true), tracing information on the progress of the algorithm is produced. Higher values may produce more tracing information.- centroid
A string specifying which type of centroid should be used when applying kmeans on a QTS sample. Choices are
mean
andmedoid
. Defaults tomean
.- dissimilarity
A string specifying which type of dissimilarity should be used when applying kmeans on a QTS sample. Choices are
l2
andpearson
. Defaults tol2
.- warping
A string specifying which class of warping functions should be used when applying kmeans on a QTS sample. Choices are
none
,shift
,dilation
andaffine
. Defaults toaffine
.
Value
An object of class stats::kmeans
if the input x
is NOT of class
qts_sample
. Otherwise, an object of class kma_qts
which is
effectively a list with three components:
qts_aligned
: An object of class qts_sample storing the sample of aligned QTS;qts_centers
: A list of objects of class qts representing the centers of the clusters;best_kma_result
: An object of class fdacluster::kma storing the results of the best k-mean alignment result among all initialization that were tried.