View source: R/parallel_vboot.R
Validate linear regression using bootstrap.
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fit |
Object from lm fit |
x |
A matrix of the predictors, each row is an observation vector. |
y |
A vector of response variable. It should be quantitative for lineal regression, a factor with two levels for logistic regression or a two-column matrix with columns named 'time' and 'status' for cox regression. |
s |
Value of the penalty parameter "lambda" selected from the original 'cv.glmnet'. |
gamma |
Value of "gamma" parameter selected for relaxed model |
nfolds |
Number of folds for cross validation as in 'cv.glmnet'. |
B |
Number of bootsrap samples |
cv_replicates |
Number of replicates for the cross-validation step |
n_cores |
number of cores to use in parallel. Default detectCores()-1 |
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