Depricated function to compute optimal value of regularization parameter based on K-fold cross-validation — multiclass_cv • multiclassreg

Depricated function to compute optimal value of regularization parameter based on K-fold cross-validation

multiclass_cv(
  fit,
  Kfold = 5,
  nweight = NULL,
  weighting = TRUE,
  wtype = "size",
  type = "MSFE",
  l1length = 100,
  normalize = TRUE
)

Arguments

fit: fitted object returned from multiclass_reg()
Kfold: K-fold cross-validation
nweight: vector of length K indicating weights for MSFE measure
type: MSFE or MAFE
l1length: length sparsity grid l1 penalty
asym: flag: asymmetric forecast error measure or not

Value

A list with the following components

lambda_opt: Selected value of the regularization parameter via BIC
bhat_opt: Estimated coefficients selected via BIC