paths.plot: Plot the solution paths.

In andrewchay/aft-hd: Fit sparse weighted linear regression model using coordinate descent algorithm

Description

This function plots the solution paths of LASSO and MCP solutions.

Usage

paths.plot(result, penalty = "MCP", n_kappa = 1)

Arguments

result	a list consists of result from weighted.sparsenet
penalty	Character to specify the penalty. Possible values are "MCP", "SCAD", "LASSO" or "adaptive". Specify whether to plot solution paths for MCP, SCAD, LASSO or adaptive LASSO penalties.
n_kappa	If penalty is "MCP", "SCAD" or "adaptive", the function plots the paths corresponding to the n_kappath kappa.

Value

Generate the paths plots.

Author(s)

Hao Chai

Examples

X = matrix(rnorm(8000), nrow = 20)
beta0 = c(rep(10, 5), rep(0, 395))
y = rnorm(20) + X %*% beta0
delta = rep(1, 20)
result = weighted.sparsenet(X, y, delta, n_kappa = 40, kappa0 = 0.99)
paths.plot(result, n_kappa = 20)

andrewchay/aft-hd documentation built on May 14, 2019, 8:21 a.m.