modeltime: nnetar_fit_impl – R documentation

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nnetar_fit_impl

Low-Level NNETAR function for translating modeltime to forecast

Low-Level NNETAR function for translating modeltime to forecast

nnetar_fit_impl(
  x,
  y,
  period = "auto",
  p = 1,
  P = 1,
  size = 10,
  repeats = 20,
  decay = 0,
  maxit = 100,
  ...
)

`x`	A dataframe of xreg (exogenous regressors)
`y`	A numeric vector of values to fit
`period`	A seasonal frequency. Uses "auto" by default. A character phrase of "auto" or time-based phrase of "2 weeks" can be used if a date or date-time variable is provided.
`p`	Embedding dimension for non-seasonal time series. Number of non-seasonal lags used as inputs. For non-seasonal time series, the default is the optimal number of lags (according to the AIC) for a linear AR(p) model. For seasonal time series, the same method is used but applied to seasonally adjusted data (from an stl decomposition).
`P`	Number of seasonal lags used as inputs.
`size`	Number of nodes in the hidden layer. Default is half of the number of input nodes (including external regressors, if given) plus 1.
`repeats`	Number of networks to fit with different random starting weights. These are then averaged when producing forecasts.
`decay`	Parameter for weight decay. Default 0.
`maxit`	Maximum number of iterations. Default 100.
`...`	Additional arguments passed to `forecast::nnetar`

The Tidymodels Extension for Time Series Modeling

v0.5.1

MIT + file LICENSE

Authors

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

Initial release