tune_u_joint: Tuning envelope dimension jointly by BIC in TEMM.

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

Description

Tuning envelope dimension jointly by BIC in TEMM.

Usage

tune_u_joint(u_candi, K, X, iter.max = 500, stop = 0.001, trueY = NULL)

Arguments

u_candi	A list of length M containing candidate envelope dimension for each mode.
K	Nuber of clusters, greater than or equal to 2.
X	The tensor for clustering, should be array tpye, the last dimension is the sample size n.
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.

Value

opt.u	Optimal envelope dimension selected.
opt.id	Estimated labels fitted by TEMM with the optimal envelope dimension.
opt.Mu	Estimated cluster means fitted by TEMM with the optimal envelope dimension.
bic	BIC value.

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))
  mytune = tune_u_joint(u_candi=list(1:2,1:2),K=2,A)

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