# Find model parameters from models with special components

Source:`R/find_parameters_other.R`

`find_parameters.averaging.Rd`

Returns the names of model parameters, like they typically
appear in the `summary()`

output.

## Usage

```
# S3 method for class 'averaging'
find_parameters(x, component = c("conditional", "full"), flatten = FALSE, ...)
# S3 method for class 'betareg'
find_parameters(
x,
component = c("all", "conditional", "precision", "location", "distributional",
"auxiliary"),
flatten = FALSE,
...
)
# S3 method for class 'DirichletRegModel'
find_parameters(
x,
component = c("all", "conditional", "precision", "location", "distributional",
"auxiliary"),
flatten = FALSE,
...
)
# S3 method for class 'mjoint'
find_parameters(
x,
component = c("all", "conditional", "survival"),
flatten = FALSE,
...
)
# S3 method for class 'glmx'
find_parameters(
x,
component = c("all", "conditional", "extra"),
flatten = FALSE,
...
)
```

## Arguments

- x
A fitted model.

- component
Should all predictor variables, predictor variables for the conditional model, the zero-inflated part of the model, the dispersion term or the instrumental variables be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variable (so called fixed-effects regressions). May be abbreviated. Note that the

*conditional*component is also called*count*or*mean*component, depending on the model.- flatten
Logical, if

`TRUE`

, the values are returned as character vector, not as list. Duplicated values are removed.- ...
Currently not used.

## Value

A list of parameter names. The returned list may have following elements:

`conditional`

, the "fixed effects" part from the model.`full`

, parameters from the full model.

## Examples

```
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_parameters(m)
#> $conditional
#> [1] "(Intercept)" "wt" "cyl" "vs"
#>
```