- data
Continuous, Categorical ot Mixed data set
- nclusrange
An integer vector with the range of numbers of clusters which are to be compared by the cluster validity criteria. Note: the number of clusters should be greater than one
- ndimrange
An integer vector with the range of dimensions which are to be compared by the cluster validity criteria
- method
Specifies the method. Options are RKM
for reduced K-means, FKM
for factorial K-means, mixedRKM
for mixed reduced K-means, mixedFKM
for mixed factorial K-means, MCAk
for MCA K-means, iFCB
for Iterative Factorial Clustering of Binary variables and clusCA
for Cluster Correspondence Analysis
- criterion
One of asw
, ch
or crit
. Determines whether average silhouette width, Calinski-Harabasz index or objective value of the selected method is used (default = "asw")
- dst
Specifies the data used to compute the distances between objects. Options are full
for the original data (after possible scaling) and low
for the object scores in the low-dimensional space (default = "full")
- alpha
Adjusts for the relative importance of (mixed) RKM and FKM in the objective function; alpha = 1
reduces to PCA, alpha = 0.5
to (mixed) reduced K-means, and alpha = 0
to (mixed) factorial K-means
- alphak
Non-negative scalar to adjust for the relative importance of MCA (alphak = 1
) and K-means (alphak = 0
) in the solution (default = .5). Works only in combination with method = "MCAk"
- center
A logical value indicating whether the variables should be shifted to be zero centered (default = TRUE)
- scale
A logical value indicating whether the variables should be scaled to have unit variance before the analysis takes place (default = TRUE)
- rotation
Specifies the method used to rotate the factors. Options are none for no rotation, varimax for varimax rotation with Kaiser normalization and promax for promax rotation (default = "none")
- nstart
Number of starts (default = 100)
- smartStart
If NULL
then a random cluster membership vector is generated. Alternatively, a cluster membership vector can be provided as a starting solution
- seed
An integer that is used as argument by set.seed()
for offsetting the random number generator when smartStart = NULL. The default value is NULL.
- x
For the print
method, a class of clusmca
- object
For the summary
method, a class of clusmca
- mth
For the fitted
method, a character string that specifies the type of fitted value to return: "centers"
for the observations center vector, or "class"
for the observations cluster membership value
- ...
Not used