# Find names of model parameters from generalized additive models

Source:`R/find_parameters_gam.R`

`find_parameters.gamlss.Rd`

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

output.

## Usage

```
# S3 method for gamlss
find_parameters(x, flatten = FALSE, ...)
# S3 method for gam
find_parameters(
x,
component = c("all", "conditional", "smooth_terms", "location"),
flatten = FALSE,
...
)
```

## Arguments

- x
A fitted model.

- flatten
Logical, if

`TRUE`

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

- component
Which type of parameters to return, such as parameters for the conditional model, the zero-inflated part of the model, the dispersion term, the instrumental variables or marginal effects be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variables (so called fixed-effects regressions), or models with marginal effects from mfx. May be abbreviated. Note that the

*conditional*component is also called*count*or*mean*component, depending on the model. There are three convenient shortcuts:`component = "all"`

returns all possible parameters. If`component = "location"`

, location parameters such as`conditional`

,`zero_inflated`

,`smooth_terms`

, or`instruments`

are returned (everything that are fixed or random effects - depending on the`effects`

argument - but no auxiliary parameters). For`component = "distributional"`

(or`"auxiliary"`

), components like`sigma`

,`dispersion`

,`beta`

or`precision`

(and other auxiliary parameters) are returned.

## Value

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

`conditional`

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

, the smooth parameters.

## Examples

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