cbird (version 1.0)

EstScore:

Description

This function estimates components scores for each subject using the result of CLUSBIRD.

Usage

EstScore(X, A, mu, N.ite=10000, N.random=1, show.random.ite=FALSE,
oblique=FALSE, mc.cores=1)

Arguments

X

Binary data matrix (N * D).

A

Loading matrix (D * L) estimated by cbird.

mu

A D-length mean vector estimated by cbird.

N.ite

The number of maximum of iterations for the EM algorithm.

N.random

The number of random sets of parameters for initial random starts.

show.random.ite

If "TRUE", the number of each iteration is shown on the R console.

oblique

If "TRUE", the oblique component scores F are estimated. The default is "FALSE".

mc.cores

If "parallel" package has been installed, "EstScore" adopts a multithread process for multiple initial random starts. If "mc.cores"=1, "parallel" package is not needed, and a single core process is conducted.

Value

F

An estimated component score matrix (N * D) containing scores for subjects.

n.ite

The number of iteration needed for convergence.

loss

The value of loss function used in ALS algorithm

References

Yamamoto, M. and Hayashi, K. (2015). Clustering of multivariate binary data with dimension reduction via L1-regularized maximization. Pattern Recognition, 48, 3959-3968.

Examples

##See the example of the function "cbird".