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BS_SPSP Function to conduct residual bootstrap and SPSP selection method. It generate bootstrap_rep copies of different bootstrap samples through the residual bootstrap and obtain bootstrap models and estimates. It supports differen method embeded in the SPSP function, such as approach lasso.glmnet, adalasso.glmnet, adalassoCV.glmnet.

BS_SPSP.Rd

BS_SPSP Function to conduct residual bootstrap and SPSP selection method. It generate bootstrap_rep copies of different bootstrap samples through the residual bootstrap and obtain bootstrap models and estimates. It supports differen method embeded in the SPSP function, such as approach lasso.glmnet, adalasso.glmnet, adalassoCV.glmnet.

Usage

BS_SPSP(
  x,
  y,
  intercept = FALSE,
  family = "gaussian",
  fitfun.SP = adalassoCV.glmnet,
  args.fitfun.SP = list(),
  bootstrap_rep = 1000,
  parallel = FALSE,
  standardize = FALSE,
  ...
)

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.

fitfun.SP

A function to obtain the solution paths for the SPSP algorithm. This function takes the arguments x, y, family as above, and additionally the standardize and intercept and others in glmnet or lars. The function fit the model with lasso, adaptive lasso, or ridge regression to return the solution path of the corresponding penalized likelihood approach.

args.fitfun.SP

A named list containing additional arguments that are passed to the fitting function; see also argument args.fitfun.SP in do.call.

bootstrap_rep

bootstrap times.

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.

standardize

logical argument. Should conduct standardization before the estimation.

...

Additional optional arguments.