Validate glmnet linear regression using bootstrap.
# S3 method for elnet
vboot(fit, x, y, s, nfolds = 5, B = 200,
cv_replicates = 100, lambda = TRUE, n_cores = max(1,
parallel::detectCores() - 1))Object from glmnet fit.
A matrix of the predictors, each row is an observation vector.
A vector of response variable. Should be numeric.
Value of the penalty parameter "lambda" selected from the original 'cv.glmnet'.
Number of folds for cross validation as in 'cv.glmnet'.
Number of bootsrap samples.
Number of replicates for the cross-validation step.
By default, the validation is adjusted using 'lambda.1se' which has error within 1 standard error of the best model. If 'FALSE' the 'lambda.min' referered to the lowest CV error will be used.
number of cores to use in parallel. Default detectCores()-1.