Description
Robust Selection Algorithm.
Description
An implementation of algorithms for estimation of the graphical lasso regularization parameter described in Pedro Cisneros-Velarde, Alexander Petersen and Sang-Yun Oh (2020) <http://proceedings.mlr.press/v108/cisneros20a.html>.
README.md
robsel
An R package of Robust Selection algorithm for estimation of the graphical lasso regularization parameter.
Installation
You can install the released version of robsel from CRAN with:
install.packages("robsel")
Example
This is a basic example which shows you how to solve a common problem:
library(robsel)
## basic example code
x <- matrix(rnorm(100*5),ncol=5)
#Estimate lambda for glasso
lambda <- robsel(x, alpha=0.9, B=200)
lambda
#> [1] 0.1561845
#Use glasso directly with robsel estimate
glasso.model <- robsel.glasso(x, alpha=0.9)
glasso.model
#> $alpha
#> [1] 0.9
#>
#> $lambda
#> [1] 0.1596663
#>
#> $Sigma
#> $Sigma[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.04954034 0.02769511 0.000000 -0.08435207 0.000000
#> [2,] 0.02769511 1.25358486 0.000000 -0.00222587 0.000000
#> [3,] 0.00000000 0.00000000 1.092117 0.00000000 0.000000
#> [4,] -0.08435207 -0.00222587 0.000000 1.12448050 0.000000
#> [5,] 0.00000000 0.00000000 0.000000 0.00000000 1.246764
#>
#>
#> $Omega
#> $Omega[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.95913305 -0.02106219 0.0000000 0.07190696 0.0000000
#> [2,] -0.02106219 0.79817757 0.0000000 0.00000000 0.0000000
#> [3,] 0.00000000 0.00000000 0.9156528 0.00000000 0.0000000
#> [4,] 0.07190696 0.00000000 0.0000000 0.89469360 0.0000000
#> [5,] 0.00000000 0.00000000 0.0000000 0.00000000 0.8020765
#Using robsel with multiple confidence level alpha
robsel(x, alpha=c(0.1,0.9))
#> [1] 0.3266095 0.1571961
robsel.glasso(x, alpha=c(0.1,0.9))
#> $alpha
#> [1] 0.1 0.9
#>
#> $lambda
#> [1] 0.3179958 0.1588493
#>
#> $Sigma
#> $Sigma[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.20787 0.000000 0.000000 0.00000 0.000000
#> [2,] 0.00000 1.411914 0.000000 0.00000 0.000000
#> [3,] 0.00000 0.000000 1.250446 0.00000 0.000000
#> [4,] 0.00000 0.000000 0.000000 1.28281 0.000000
#> [5,] 0.00000 0.000000 0.000000 0.00000 1.405093
#>
#> $Sigma[[2]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.04872328 0.028512174 0.0000 -0.085169133 0.000000
#> [2,] 0.02851217 1.252767801 0.0000 -0.002315537 0.000000
#> [3,] 0.00000000 0.000000000 1.0913 0.000000000 0.000000
#> [4,] -0.08516913 -0.002315537 0.0000 1.123663436 0.000000
#> [5,] 0.00000000 0.000000000 0.0000 0.000000000 1.245947
#>
#>
#> $Omega
#> $Omega[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.8279038 0.0000000 0.0000000 0.0000000 0.0000000
#> [2,] 0.0000000 0.7082583 0.0000000 0.0000000 0.0000000
#> [3,] 0.0000000 0.0000000 0.7997144 0.0000000 0.0000000
#> [4,] 0.0000000 0.0000000 0.0000000 0.7795387 0.0000000
#> [5,] 0.0000000 0.0000000 0.0000000 0.0000000 0.7116965
#>
#> $Omega[[2]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.96003670 -0.02171539 0.0000000 0.07272214 0.0000000
#> [2,] -0.02171539 0.79872675 0.0000000 0.00000000 0.0000000
#> [3,] 0.00000000 0.00000000 0.9163384 0.00000000 0.0000000
#> [4,] 0.07272214 0.00000000 0.0000000 0.89545824 0.0000000
#> [5,] 0.00000000 0.00000000 0.0000000 0.00000000 0.8026025