doubleres {phd} | R Documentation |
Permutation test based on double residualization
Description
Provides a class of tests for testing in high-dimensional linear models. The tests are robust against heteroscedasticity and non-normality. They often provide good type I error control even under anti-sparsity.
Usage
doubleres(y,X,X1,nperm=2E4,lambda="lambda.min",flip="FALSE",nfolds=10)
Arguments
y |
The values of the outcome. |
X |
The design matrix.
If the covariate of interest is included in |
X1 |
n-vector with the (1-dimensional) covariate of interest.
|
nperm |
The number of random permutations (or sign-flipping maps) used by the test |
lambda |
The penalty used in the ridge regressions. Default is |
flip |
Default is "FALSE", which means that permutation is used. If "TRUE", then sign-flipping is used. |
nfolds |
The number of folds used in the cross-validation (in case lambda is determined using cross-validation). |
Value
A two-sided p-value.
Examples
set.seed(5193)
n=30
X <- matrix(nr=n,nc=60,rnorm(n*60))
y <- X[,1]+X[,2]+X[,3] + rnorm(n,mean=0) #H0: first coefficient=0. So H0 is false
doubleres(y, X, nperm=2000, lambda=100,flip="FALSE")