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nnetar_params

Tuning Parameters for NNETAR Models

Tuning Parameters for NNETAR Models

num_networks(range = c(1L, 100L), trans = NULL)

`range`	A two-element vector holding the defaults for the smallest and largest possible values, respectively.
`trans`	A `trans` object from the `scales` package, such as `scales::log10_trans()` or `scales::reciprocal_trans()`. If not provided, the default is used which matches the units used in `range`. If no transformation, `NULL`.

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.

num_networks()

The Tidymodels Extension for Time Series Modeling

v0.5.1

MIT + file LICENSE

Authors

Matt Dancho [aut, cre], Business Science [cph]

Initial release