print.select

An object with S3 class <code>"select"</code>

Print the information about the model usage, graph dimension, model selection criterion, sparsity level of the optimal graph

The package "flare" provides the implementation of a
        family of Lasso variants including Dantzig Selector, LAD Lasso,
        SQRT Lasso, Lq Lasso for estimating high dimensional sparse
        linear model. We adopt the alternating direction method of
        multipliers and convert the original optimization problem into
        a sequential L1 penalized least square minimization problem,
        which can be efficiently solved by combining the linearization
        and the efficient coordinate descent algorithm. The computation
        is memory-optimized using the sparse matrix output. Besides the
        sparse linear model estimation, we also provide the extension
        of these Lasso variants to sparse Gaussian graphical model
        estimation including TIGER and CLIME using either L1 or
        adaptive penalty.

print.select: Print function for S3 class "select"

Description

Usage

Arguments

See Also