Skip to contents

Tuning Parameters for ARIMA Models

Source: R/dials-arima_params.R
arima_params.Rd

Tuning Parameters for ARIMA Models

Usage

non_seasonal_ar(range = c(0L, 5L), trans = NULL)

non_seasonal_differences(range = c(0L, 2L), trans = NULL)

non_seasonal_ma(range = c(0L, 5L), trans = NULL)

seasonal_ar(range = c(0L, 2L), trans = NULL)

seasonal_differences(range = c(0L, 1L), trans = NULL)

seasonal_ma(range = c(0L, 2L), trans = NULL)

Arguments

range

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.

trans

A trans object from the scales package, such as scales::transform_log10() or scales::transform_reciprocal(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

Details

The main parameters for ARIMA models are:

  • non_seasonal_ar: The order of the non-seasonal auto-regressive (AR) terms.

  • non_seasonal_differences: The order of integration for non-seasonal differencing.

  • non_seasonal_ma: The order of the non-seasonal moving average (MA) terms.

  • seasonal_ar: The order of the seasonal auto-regressive (SAR) terms.

  • seasonal_differences: The order of integration for seasonal differencing.

  • seasonal_ma: The order of the seasonal moving average (SMA) terms.

Examples

ets_model()
#> ETS Model (qualitative)
#> 6 possible values include:
#> 'ZZZ', 'XXX', 'YYY', 'CCC', 'PPP', and 'FFF'

non_seasonal_ar()
#> Non-seasonal AR Term (quantitative)
#> Range: [0, 5]

non_seasonal_differences()
#> Non-seasonal Differencing Term (quantitative)
#> Range: [0, 2]

non_seasonal_ma()
#> Non-seasonal MA Term (quantitative)
#> Range: [0, 5]