coef.rlassoEffects: Coefficients from S3 objects 'rlassoEffects'

In hdm: High-Dimensional Metrics

Coefficients from S3 objects rlassoEffects

Description

Method to extract coefficients from objects of class rlassoEffects

Usage

## S3 method for class 'rlassoEffects'
coef(
  object,
  complete = TRUE,
  selection.matrix = FALSE,
  include.targets = FALSE,
  ...
)

Arguments

object	an object of class rlassoEffects, usually a result of a call rlassoEffect or rlassoEffects.
complete	general option of the function coef.
selection.matrix	if TRUE, a selection matrix is returned that indicates the selected variables from each auxiliary regression. Default is set to FALSE.
include.targets	if FALSE (by default) only the selected control variables are listed in the selection.matrix. If set to TRUE, the selection matrix will also indicate the selection of the target coefficients that are specified in the rlassoEffects call.
...	further arguments passed to functions coef or print.

Details

Printing coefficients and selection matrix for S3 object rlassoEffects. Interpretation of entries in the selection matrix

• "-" indicates a target variable,

• "x" indicates that a variable has been selected with rlassoEffects (coefficient is different from zero),

• "." indicates that a variable has been de-selected with rlassoEffects (coefficient is zero).

Examples

library(hdm)
set.seed(1)
n = 100 #sample size
p = 100 # number of variables
s = 7 # number of non-zero variables
X = matrix(rnorm(n*p), ncol=p)
colnames(X) <- paste("X", 1:p, sep="")
beta = c(rep(3,s), rep(0,p-s))
y = 1 + X%*%beta + rnorm(n)
data = data.frame(cbind(y,X))
colnames(data)[1] <- "y"
lasso.effect = rlassoEffects(X, y, index=c(1,2,3,50), 
                             method = "double selection")
coef(lasso.effect) # standard use of coef() - without selection matrix
# with selection matrix
coef(lasso.effect, selection.matrix = TRUE)
# prettier output with print_coef (identical options as coef())
print_coef(lasso.effect, selection.matrix = TRUE) 

hdm documentation built on May 29, 2024, 3:35 a.m.