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TensorClustering

Performs model-based tensor clustering methods including the Tensor Envelope Mixture Model (TEMM), Doubly-Enhanced EM (DEEM) algorithm and Tensor Gaussian Mixture Model (TGMM). TEMM is proposed in the paper “Tensor Envelope Mixture Model For Simultaneous Clustering and Multiway Dimension Reduction” published in Biometrics by Deng and Zhang (2021). DEEM is proposed in the paper “A Doubly-Enhanced EM Algorithm for Model-Based Tensor Clustering” published in the Journal of the American Statistical Association by Mai, Zhang, Pan and Deng (2021).

Installation

The TensorClustering package can be installed, directly from CRAN:

install.packages("TensorClustering")
library(TensorClustering)

It can also be installed from GitHub, using the devtools library:

install.packages("devtools")
library(devtools)
devtools::install_github("azuryee/TensorClustering")
library(TensorClustering)

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Version

Install

install.packages('TensorClustering')

Monthly Downloads

146

Version

1.0.2

License

MIT + file LICENSE

Maintainer

Kai Deng

Last Published

June 26th, 2021

Functions in TensorClustering (1.0.2)

tune_u_joint

Tuning envelope dimension jointly by BIC in TEMM.
TEMM

Fit the Tensor Envelope Mixture Model (TEMM)
TGMM

Fit the Tensor Gaussian Mixture Model (TGMM)
tune_K

Select the number of clusters K in DEEM
tune_lamb

Parameter tuning in enhanced E-step in DEEM
DEEM

Doubly-enhanced EM algorithm
tune_u_sep

Tuning envelope dimension separately by BIC in TEMM.