I noticed that one small difference between Statsforecast and MLforecast is that in cross validation, the MLforecast allows for refit param to take integer, whereas in statsforecast it is simply true / false, which means I either refit after every single step or I do not refit at all during the CV.
• Is this by design ?
• Is it possible to set up a daily refit in statsforecast same as in MLforecast, where I can simply set: refit = 24 ?
cv_df = sf.cross_validation(
df = df,
h = h,
level = [90],
step_size = step_size,
test_size = test_size_adjusted,
# input_size = 90*96,
n_windows = None,
refit = False,
fitted = True
)