HRClusterpath
is a R
-package which provides tools for the variable clustering of Husler-Reiss models, specially using the graphical models structure.
Installation
To install the package, one can write this in the R
-terminal :
remotes::install_github("alxkpl/HRClusterpath")
Usage
This section gives an overview of the package’s tools.
Clusterpath algorithm for hierarchical clustering
The first method you can use with the package is a hierarchical clustering (for variables) using a Clusterpath algorithm applied to the likelihood of the precision matrix of the Husler Reiss graphical model with a fused-Lasso penalty.
You can use :
-
get_cluster
to get optimal cluster with fixed parameter \(\lambda\) and estimated variogram \(\hat \Gamma\) with customizable weights. -
HR_Clusterpath
that build a list of optimal results with a grid of \(\lambda\) and the standards exponnential weights. -
gg_cluster
which provides the dendrogram induced by the results of theHR_Clusterpath
function. - and others functions to analyze the results.