Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/cv.grpregOverlap.R
Performs k-fold cross validation for penalized regression models with overlapping grouped covariates over a grid of values for the regularization parameter lambda.
1 | cv.grpregOverlap(X, y, group, ...)
|
X |
The design matrix, without an intercept, as in |
y |
The response vector (or matrix), as in |
group |
A list of vectors containing group information, as in |
... |
Additional arguments to either |
This function is built upon cv.grpreg
. The class can directly call
plot
function implemented for class cv.grpreg
.
An object with S3 class "cv.grpregOverlap"
, which inherits from class "cv.grpreg"
.
The following variables are contained in the class (adopted from cv.grpreg
).
cve |
The error for each value of |
cvse |
The estimated standard error associated with each value of for |
lambda |
The sequence of regularization parameter values along which the cross-validation error was calculated. |
fit |
The fitted |
min |
The index of |
lambda.min |
The value of |
null.dev |
The deviance for the intercept-only model. |
pe |
If |
Yaohui Zeng and Patrick Breheny
Maintainer: Yaohui Zeng <yaohui-zeng@uiowa.edu>
Breheny P (2014). R package 'grpreg'. https://CRAN.R-project.org/package=grpreg/grpreg.pdf
grpregOverlap
, predict.grpregOverlap
, summary
, and cv.grpreg
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## linear regression, a simulation demo.
set.seed(123)
group <- list(gr1 = c(1, 2, 3),
gr2 = c(1, 4),
gr3 = c(2, 4, 5),
gr4 = c(3, 5),
gr5 = c(6))
beta.latent.T <- c(5, 5, 5, 0, 0, 0, 0, 0, 5, 5, 0) # true latent coefficients.
# beta.T <- c(5, 5, 10, 0, 5, 0), true variables: 1, 2, 3, 5; true groups: 1, 4.
X <- matrix(rnorm(n = 6*100), ncol = 6)
X.latent <- expandX(X, group)
y <- X.latent %*% beta.latent.T + rnorm(100)
cvfit <- cv.grpregOverlap(X, y, group, penalty = 'grMCP')
summary(cvfit)
plot(cvfit)
par(mfrow=c(2,2))
plot(cvfit, type="all")
|
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