Create a partial response or effect plot of a trained model.

## Usage

```
partial(
mod,
x.var = NULL,
constant = NULL,
variable_length = 100,
values = NULL,
newdata = NULL,
plot = FALSE,
type = "response",
...
)
# S4 method for ANY
partial(
mod,
x.var = NULL,
constant = NULL,
variable_length = 100,
values = NULL,
newdata = NULL,
plot = FALSE,
type = "response",
...
)
partial.DistributionModel(mod, ...)
```

## Arguments

- mod
A trained

`DistributionModel`

object with`fit_best`

model within.- x.var
A character indicating the variable for which a partial effect is to be calculated.

- constant
A numeric constant to be inserted for all other variables. Default calculates a mean per variable.

- variable_length
numeric The interpolation depth (nr. of points) to be used (Default:

`100`

).- values
numeric Directly specified values to compute partial effects for. If this parameter is set to anything other than

`NULL`

, the parameter`"variable_length"`

is ignored (Default:`NULL`

).- newdata
An optional data.frame with provided data for partial estimation (Default:

`NULL`

).- plot
A

`logical`

indication of whether the result is to be plotted?- type
A specified type, either

`'response'`

or`'predictor'`

. Can be missing.- ...
Other engine specific parameters.

## Value

A data.frame with the created partial response.