simplelasso estimates a model using LASSO and
returns a sparse structure.
Cross-validation can be used to select best covariates
Should cross-validation be performed? TRUE or FALSE
Number of folds for cross-validation. Ignored if
Boolean indicating whether some factor variables should be dropped
A list of three elements.
output$model returns the model.
output$plot returns a plot. If
crossvalidation = F,
coefficients values when $\lambda$ penalization term
evolves is represented.
crossvalidation = T, the RMSE is represented with respect to the
number of variables with non-zero weight
output$coeff returns the coefficient values returned by the LASSO
(or the coefficients of the RMSE-minimizing model if
crossvalidation = T)
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