thresh_est: Threshold estimation

In HSDiC: Homogeneity and Sparsity Detection Incorporating Prior Constraint Information

Description

Function to implement the soft-, MCP, SCAD thresholding rule in the ADMM method.

Usage

thresh_est(z, lambda, tau, a = 3, penalty = c("MCP", "SCAD", "lasso"))

Arguments

z	a vector where the function is to be evaluated.
lambda	a number representing a tuning parameter.
tau	the penalty parameter in the ADMM method.
a	the tuning parameter of the MCP/SCAD penalty (see details). Default is 3 for MCP and 3.7 for SCAD.
penalty	The penalty to be applied to the model. Either "lasso" (the default), "SCAD", or "MCP".

Value

A vector containing the threshlding values at z.

References

'Pairwise Fusion Approach Incorporating Prior Constraint Information' by Yaguang Li

HSDiC documentation built on May 1, 2019, 8:05 p.m.