get.csuv.final.mod: Helper function, please do not use it
In CSUV: Combined Selection and Uncertainty Visualiser (CSUV)

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
)

`X`	covariates (n times p matrix, n: number of entries, p: number of covariates)
`Y`	response (vector with n entries)
`intercept`	TRUE to fit the data with an intercept, FALSE to fit the data without an intercept
`unique.fit`	from get.csuv.unique.fit
`selection.criterion`	= c("mse", "ebic"). Measure to select fitted models in subsampling dataset. "mse" is mean square error and "ebic" is extended BIC. Default is mse
`coef.est.method`	method to estimate the coefficients of covariates after variable selection. User can provide his/her function. Default is ordinary least square
`q`	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)
`method.names`	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
`B`	number of subsampling. Default is 100