vboot.elnet: Internal bootstraping validation linear glmnet model

Description Usage Arguments

View source: R/parallel_vboot.R

Description

Validate glmnet linear regression using bootstrap.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
## S3 method for class 'elnet'
vboot(
  fit,
  x,
  y,
  s,
  gamma = NULL,
  nfolds = 5,
  B = 200,
  cv_replicates = 100,
  n_cores = max(1, parallel::detectCores() - 1)
)

Arguments

fit

Object from glmnet fit

x

A matrix of the predictors, each row is an observation vector.

y

A vector of response variable. Should be numeric

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


Ancamar/bootValidation documentation built on April 26, 2020, 11:39 a.m.