Helper function, please do not use it
get.csuv.final.mod(
X,
Y,
intercept,
unique.fit,
selection.criterion,
coef.est.method = lm.ols,
q,
method.names,
B
)covariates (n times p matrix, n: number of entries, p: number of covariates)
response (vector with n entries)
TRUE to fit the data with an intercept, FALSE to fit the data without an intercept
from get.csuv.unique.fit
= c("mse", "ebic"). Measure to select fitted models in subsampling dataset. "mse" is mean square error and "ebic" is extended BIC. Default is mse
method to estimate the coefficients of covariates after variable selection. User can provide his/her function. Default is ordinary least square
percentile of fitted models used per each subsampling in CSUV, according to the selection criterion on out-of-sample data in ascending order. Default is q = 0 (only the fitted model with the lowest MSE in a subsampling data is used)
vector of method names to be used in CSUV. Choose among "lasso", "elastic", "relaxo", "mcp" and "scad". Default is to use all methods listed above
number of subsampling. Default is 100
a list of current fit