c(person(given = "Kai",
family = "Deng",
role = c("aut","cre"),
email = "kd18h@stat.fsu.edu"),
person(given = "Yuqing",
family = "Pan",
role = "aut",
email = "yuqing.pan@stat.fsu.edu"),
person(given = "Xin",
family = "Zhang",
role = "aut",
email = "henry@stat.fsu.edu"),
person(given = "Qing",
family = "Mai",
role = "aut",
email = "mai@stat.fsu.edu"))
Performs model-based tensor clustering methods including Tensor Gaussian Mixture Model (TGMM) and Tensor Envelope Mixture Model (TEMM) by Deng and Zhang (2021, tentatively accepted by Biometrics), Doubly-Enhanced EM (DEEM) algorithm by Mai, Zhang, Pan and Deng (2021) <arXiv:2012.10032>.
MASS, tensr, rTensor, TRES, abind, combinat, pracma, stats,
mvtnorm, Rcpp
Kai Deng [aut, cre],
Yuqing Pan [aut],
Xin Zhang [aut],
Qing Mai [aut]

Performs model-based tensor clustering methods including Tensor Gaussian Mixture Model (TGMM), Tensor Envelope Mixture Model (TEMM) by Deng and Zhang (2021) <DOI: 10.1111/biom.13486>, Doubly-Enhanced EM (DEEM) algorithm by Mai, Zhang, Pan and Deng (2021) <DOI: 10.1080/01621459.2021.1904959>.

Tensor Noise Reduction and Completion Methods
Chanwoo Lee <chanwoo.lee@wisc.edu>, Miaoyan Wang <miaoyan.wang@wisc.edu>
pracma, methods, utils, tensorregress, MASS
Efficient algorithms for tensor noise reduction and completion. This package includes a suite of parametric and nonparametric tools for estimating tensor signals from noisy, possibly incomplete observations. The methods allow a broad range of data types, including continuous, binary, and ordinal-valued tensor entries. The algorithms employ the alternating optimization. The detailed algorithm description can be found in the following three references.
Chanwoo Lee and Miaoyan Wang. Tensor denoising and completion
based on ordinal observations. ICML, 2020.
http://proceedings.mlr.press/v119/lee20i.html Chanwoo Lee and
Miaoyan Wang. Beyond the Signs: Nonparametric tensor completion
via sign series. 2021.  https://arxiv.org/abs/2102.00384
Chanwoo Lee, Lexin Li, Hao Helen Zhang, and Miaoyan Wang.
Nonparametric trace regression in high dimensions via sign
series representation. 2021. https://arxiv.org/abs/2105.01783