knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
This vignette illustrate the basic usage of the robsel
package to estimate of the regularization parameter for Graphical Lasso.
We use a 100-by-5 matrix from generate from normal distribution.
x <- matrix(rnorm(100*5),ncol=5)
robsel
functionsThe function robsel
estimates $\lambda$, a regularization parameter for Graphical Lasso at a prespecified confidence level $\alpha$.
library(robsel) lambda <- robsel(x) lambda
The function robsel.glasso
returns estimates a sparse inverse covariance matrix using Graphical Lasso with regularization parameter estimated from Robust Selection
A <- robsel.glasso(x) A
We can use multiple $\alpha$ simultaneously with Robust Selection
alphas <- c(0.1, 0.5, 0.9) lambdas <- robsel(x, alphas) lambdas
robsel.fits <- robsel.glasso(x, alphas) robsel.fits
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