ANTsR (version 0.3.1)

subgradientL1Regression: Simple subgradientL1Regression function.

Description

SubgradientL1Regression solves y approx x beta

Usage

subgradientL1Regression(y, x, s = 0.01, percentvals = 0.1, nits = 100,
  betas = NA, sparval = NA)

Arguments

y

outcome variable

x

predictor matrix

s

gradient descent parameter

percentvals

percent of values to use each iteration

nits

number of iterations

betas

initial guess at solution

sparval

sparseness

Value

output has a list of summary items

Examples

# NOT RUN {
mat<-replicate(1000, rnorm(200))
y<-rnorm(200)
wmat<-subgradientL1Regression( y, mat, percentvals=0.05 )
print( wmat$resultcorr )
# }