Description Usage Arguments Value Author(s) Examples
View source: R/subgradientL1Regression.R
SubgradientL1Regression solves y approx x beta
1 2 3 4 5 6 7 8 9 | subgradientL1Regression(
y,
x,
s = 0.01,
percentvals = 0.1,
nits = 100,
betas = NA,
sparval = NA
)
|
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 |
output has a list of summary items
Avants BB
1 2 3 4 | mat<-replicate(1000, rnorm(200))
y<-rnorm(200)
wmat<-subgradientL1Regression( y, mat, percentvals=0.05 )
print( wmat$resultcorr )
|
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