Tuning Parameters for NNETAR ModelsSource:
Tuning Parameters for NNETAR Models
num_networks(range = c(1L, 100L), trans = NULL)
A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units.
transobject from the
scalespackage, such as
scales::reciprocal_trans(). If not provided, the default is used which matches the units used in
range. If no transformation,
The main parameters for NNETAR models are:
non_seasonal_ar: Number of non-seasonal auto-regressive (AR) lags. Often denoted "p" in pdq-notation.
seasonal_ar: Number of seasonal auto-regressive (SAR) lags. Often denoted "P" in PDQ-notation.
hidden_units: An integer for the number of units in the hidden model.
num_networks: Number of networks to fit with different random starting weights. These are then averaged when producing forecasts.
penalty: A non-negative numeric value for the amount of weight decay.
epochs: An integer for the number of training iterations.