# 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 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`

.

## 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'
```