plot.sim

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

Visualize the covariance matrix, the empirical covariance matrix, the adjacency matrix and the graph pattern of the true graph structure.

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. For Dantzig selector and Lq Lasso, we adopt the
        alternating direction method of multipliers (ADMM) 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. For LAD and SQRT Lasso,
        we adopt the combination of the dual smoothing and monotone
        fast iterative soft-thresholding algorithm (MFISTA). 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 (ADMM) using either
        L1 or adaptive L1 penalty.

plot.sim: Plot function for S3 class "sim"

Description

Usage

Arguments

See Also