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BS_adalasso_refit

Function to conduct residual bootstrap and adaptive lasso selection method. It generate bootstrap_rep different bootstrap samples through risidual bootstrap and obtain bootstrap models and estimates.

Usage

BS_adalasso_refit(
  x,
  y,
  intercept = FALSE,
  family = "gaussian",
  standardize = FALSE,
  refit = TRUE,
  parallel = FALSE,
  bootstrap_rep = 1000,
  ...
)

Arguments

x

The input matrix with dimensions (nobs) and (nvars). It has n rows (obs), and p columns (number of covariates).

y

Response variable. Now, SSCI only supports family="gaussian" with continuous respones y.

intercept

Should intercept(s) be fitted (default=TRUE) or set to zero (FALSE).

family

Response type. Either a character string representing one of the built-in families, or else a glm() family object.

standardize

logical argument. Should conduct standardization before the estimation.

refit

logical. Should conduct a selection + refitting procedure? TRUE, the default, asks the algorithm to conduct the refitting after variable selection.

parallel

Should parallel foreach (default=FALSE) be used to conduct bootstrapping? If TRUE, the parallel backend must be registered beforehand, such as doParallel or others.

bootstrap_rep

bootstrap times.

...

Additional optional arguments.