nnetar_fit_impl: Low-Level NNETAR function for translating modeltime to...

Description Usage Arguments

View source: R/parsnip-nnetar_reg.R

Description

Low-Level NNETAR function for translating modeltime to forecast

Usage

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

Arguments

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


modeltime documentation built on July 16, 2021, 9:08 a.m.