robsel {robsel} | R Documentation |
Robust Selection
Description
Robust Selection algorithm for estimation of the regularization parameter for Graphical Lasso
Usage
robsel(x, alpha = 0.9, B = 200)
Arguments
x |
A |
alpha |
Prespecified confidence level. Default 0.9 |
B |
Number of bootstrap sample. Default 200 |
Value
lambda
Estimation of the regularization parameter for Graphical Lasso. A vector of lambda will be return if more than 1 value of alpha is provided.
References
P Cisneros-Velarde, A Petersen and S-Y Oh (2020). Distributionally Robust Formulation and Model Selection for the Graphical Lasso. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics.
See Also
robsel.glasso
for using Graphical Lasso algorithm with estimate regularization parameter lambda from Robust Selection.
Examples
set.seed(17)
library(robsel)
x <-matrix(rnorm(50*20),ncol=20)
#Compute estimation of lambda at confidence level alpha
lambda <- robsel(x = x, alpha = 0.9, B = 200)
[Package robsel version 0.1.0 Index]