TEMM: Fit the Tensor Envelope Mixture Model (TEMM)

In azuryee/TEMM: Implement tensor envelope EM algorithm for paper "Tensor Envelope Mixture Model For Simultaneous Clustering and Multiway Dimension Reduction"

Description

Fit the Tensor Envelope Mixture Model (TEMM)

Usage

TEMM(Xn, u, K, initial = "kmeans", iter.max = 500, 
stop = 1e-3, trueY = NULL, print = FALSE)

Arguments

Xn	The tensor for clustering, should be array tpye, the last dimension is the sample size n.
u	A vector of envelope dimension
K	Nuber of clusters, greater than or equal to 2.
initial	Initialization methed for the regularized EM algorithm. Default value is "kmeans".
iter.max	Maximum number of iterations. Default value is 500.
stop	Convergence threshold of relative change in cluster means. Default value is 1e-3.
trueY	A vector of true cluster labels of each observation. Default value is NULL.
print	Whether to print information including current iteration number, ralative change in cluster means and clustering error (%) in each iteration.

Value

id	A vector of estimated labels.
pi	Estimated cluster wight.
eta	A n by K matrix of estimated membership weights.
Mu.est	A list of estimated cluster means.
SIG.est	A list of estimated covariance matrices.
Mm	Estimation of Mm defined in paper.
Nm	Estimation of Nm defined in paper.
Gamma.est	A list of estimated envelope basis.
PGamma.est	A list of envelope projection matrices.

Author(s)

Kai Deng, Xin Zhang

References

Deng, K. and Zhang, X. (2020) Tensor Envelope Mixture Model For Simultaneous Clustering and Multiway Dimension Reduction, Manuscript.

Examples

  A = array(c(rep(1,20),rep(2,20))+rnorm(40),dim=c(2,2,10))
  myfit = TEMM(A,u=c(2,2),K=2)

azuryee/TEMM documentation built on Dec. 31, 2020, 7:55 p.m.