| coef.grpSLOPE {grpSLOPE} | R Documentation |
Extract model coefficients
Description
Extract the regression coefficients from a grpSLOPE object, either on the
scale of the normalized design matrix (i.e., columns centered and scaled to unit norm),
or on the original scale.
Usage
## S3 method for class 'grpSLOPE'
coef(object, scaled = TRUE, ...)
Arguments
object |
A |
scaled |
Should the coefficients be returned for the normalized version of the design matrix? |
... |
Potentially further arguments passed to and from methods |
Details
If scaled is set to TRUE, then the coefficients are returned for the
normalized version of the design matrix, which is the scale on which they were computed.
If scaled is set to FALSE, then the coefficients are transformed to
correspond to the original (unaltered) design matrix.
In case that scaled = FALSE, an estimate for the intercept term is returned with
the other coefficients. In case that scaled = TRUE, the estimate of the intercept
is always equal to zero, and is not explicitly provided.
Value
A named vector of regression coefficients where the names signify the group that each entry belongs to
Examples
set.seed(1)
A <- matrix(rnorm(100^2), 100, 100)
grp <- rep(rep(letters[1:20]), each=5)
b <- c(rep(1, 20), rep(0, 80))
y <- A %*% b + rnorm(10)
result <- grpSLOPE(X=A, y=y, group=grp, fdr=0.1)
head(coef(result), 8)
# a_1 a_2 a_3 a_4 a_5 b_1 b_2 b_3
# 7.942177 7.979269 8.667013 8.514861 10.026664 8.963364 10.037355 10.448692
head(coef(result, scaled = FALSE), 8)
# (Intercept) a_1 a_2 a_3 a_4 a_5 b_1 b_2
# -0.4418113 0.8886878 0.8372108 0.8422089 0.8629597 0.8615827 0.9323849 0.9333445