A complete suite of computationally efficient methods for high dimensional clustering and inference problems in GLatent Models (a type of Latent Variable Gaussian graphical model). The main feature is the FORCE (FirstOrder, Certifiable, Efficient) clustering algorithm which is a fast solver for a semidefinite programming (SDP) relaxation of the Kmeans problem. For certain types of graphical models (GLatent Models), with high probability the algorithm not only finds the optimal clustering, but produces a certificate of having done so. This certificate, however, is model independent and so can also be used to certify data clustering problems. The 'GFORCE' package also contains implementations of inferential procedures for GLatent graphical models using nfold cross validation. Also included are native code implementations of other popular clustering methods such as Lloyd's algorithm with kmeans++ initialization and complete linkage hierarchical clustering. The FORCE method is due to Eisenach and Liu (2019) <arxiv:1806.00530>.
Package details 


Author  Carson Eisenach [aut, cre] 
Maintainer  Carson Eisenach <[email protected]> 
License  GPL2 
Version  0.1.4 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.