Description Usage Arguments Value References See Also
This function clusters along one way of a threeway array (as specified by margin
) while
decomposing along the other two dimensions. Four types of clusterings are allowed based on the
respective twoway slices of the array: on the overall means, row margins, column margins and the
interactions between rows and columns. Which clusterings can be fit is determined by the vector
delta
, with four binary elements. All orthogonal models are fitted.
The nonorthogonal case delta = (1, 1, 0, 0)
returns an error. See the reference for further details.
1 2 3 4 
data 
A threeway array representing the data. 
margin 
An integer giving the single subscript of 
delta 
A fourelement binary vector (logical or numeric) indicating which sumtozero constraints must be enforced. 
nclust 
A vector of length four giving the number of clusters for the overall mean, the row margins, the column margins and the interactions (in that order) respectively. Alternatively, a vector of length one, in which case all components will have the same number of clusters. 
ndim 
The required rank for the approximation of the interactions (a scalar). 
fixed 
One of 
nstart 
The number of random starts to use for the interaction clustering. 
starts 
A list containing starting configurations for the cluster membership vector. If not
supplied, random initializations will be generated (passed to 
nstart.kmeans 
The number of random starts to use in 
alpha 
Numeric value in [0, 1] which determines how the singular values are distributed
between rows and columns (passed to 
parallel 
Logical indicating whether to parallel over different starts or not
(passed to 
maxit 
The maximum number of iterations allowed in the interaction clustering. 
verbose 
Integer controlling the amount of information printed: 0 = no information, 1 = Information on random starts and progress, and 2 = information is printed after each iteration for the interaction clustering. 
method 
The method for calculating cluster agreement across random starts, passed on
to 
type 
One of 
sep.nclust 
Logical indicating how nclust should be used across different 
... 
Additional arguments passed to 
Returns an object of S3 class lsbclust
which has slots:

Object of class 

Object of class 

Object of class 

Object of class 

The function call used to create the object 

The value of 

Breakdown of the degreesoffreedom across the different subproblems 

Breakdown of the loss across subproblems 

Time taken in seconds to calculate the solution 

Matrix of cluster membership per observation for all cluster types 
Schoonees, P.C., Groenen, P.J.F., Van de Velden, M. Leastsquares Bilinear Clustering of Threeway Data. Econometric Institute Report, EI201423.
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