Tuning Parameters for Exponential Smoothing Models
Source:R/dials-ets_params.R
exp_smoothing_params.Rd
Tuning Parameters for Exponential Smoothing Models
Usage
error(values = c("additive", "multiplicative"))
trend(values = c("additive", "multiplicative", "none"))
trend_smooth(
values = c("additive", "multiplicative", "none", "additive_damped",
"multiplicative_damped")
)
season(values = c("additive", "multiplicative", "none"))
damping(values = c("none", "damped"))
damping_smooth(range = c(0, 2), trans = NULL)
smooth_level(range = c(0, 1), trans = NULL)
smooth_trend(range = c(0, 1), trans = NULL)
smooth_seasonal(range = c(0, 1), trans = NULL)
Arguments
- values
A character string of possible values.
- 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 thescales
package, such asscales::transform_log10()
orscales::transform_reciprocal()
. If not provided, the default is used which matches the units used inrange
. If no transformation,NULL
.
Details
The main parameters for Exponential Smoothing models are:
error
: The form of the error term: additive", or "multiplicative". If the error is multiplicative, the data must be non-negative.trend
: The form of the trend term: "additive", "multiplicative" or "none".season
: The form of the seasonal term: "additive", "multiplicative" or "none"..damping
: Apply damping to a trend: "damped", or "none".smooth_level
: This is often called the "alpha" parameter used as the base level smoothing factor for exponential smoothing models.smooth_trend
: This is often called the "beta" parameter used as the trend smoothing factor for exponential smoothing models.smooth_seasonal
: This is often called the "gamma" parameter used as the seasonal smoothing factor for exponential smoothing models.
Examples
error()
#> Error Term (qualitative)
#> 2 possible values include:
#> 'additive' and 'multiplicative'
trend()
#> Trend Term (qualitative)
#> 3 possible values include:
#> 'additive', 'multiplicative' and 'none'
season()
#> Season Term (qualitative)
#> 3 possible values include:
#> 'additive', 'multiplicative' and 'none'