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dTBM  

Multi-Way Spherical Clustering via Degree-Corrected Tensor Block Models
View on CRAN: Click here


Download and install dTBM package within the R console
Install from CRAN:
install.packages("dTBM")

Install from Github:
library("remotes")
install_github("cran/dTBM")

Install by package version:
library("remotes")
install_version("dTBM", "3.0")



Attach the package and use:
library("dTBM")
Maintained by
Jiaxin Hu
[Scholar Profile | Author Map]
First Published: 2022-01-15
Latest Update: 2023-06-18
Description:
Implement weighted higher-order initialization and angle-based iteration for multi-way spherical clustering under degree-corrected tensor block model. See reference Jiaxin Hu and Miaoyan Wang (2023) .
How to cite:
Jiaxin Hu (2022). dTBM: Multi-Way Spherical Clustering via Degree-Corrected Tensor Block Models. R package version 3.0, https://cran.r-project.org/web/packages/dTBM. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2022-01-15 10:02), 2.0 (2022-02-06 04:50)
Other packages that cited dTBM R package
View dTBM citation profile
Other R packages that dTBM depends, imports, suggests or enhances
Complete documentation for dTBM
Functions, R codes and Examples using the dTBM R package
Some associated functions: HCP . Tensor-class . angle_iteration . as.tensor . dim-methods . dtbm . fold . kronecker_list . peru . rand_tensor . select_r . sim_dTBM . ttl . ttm . unfold-methods . wkmeans . 
Some associated R codes: HCP.R . bricks.R . peru.R . tensor_class.R . tensor_clustering.R . tensor_product.R .  Full dTBM package functions and examples
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