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

output. For Bayesian models, the parameter
names equal the column names of the posterior samples after coercion
from `as.data.frame()`

. See the documentation for your object's class:

Bayesian models (rstanarm, brms, MCMCglmm, ...)

Generalized additive models (mgcv, VGAM, ...)

Marginal effects models (mfx)

Estimated marginal means (emmeans)

Mixed models (lme4, glmmTMB, GLMMadaptive, ...)

Zero-inflated and hurdle models (pscl, ...)

Models with special components (betareg, MuMIn, ...)

## Usage

```
find_parameters(x, ...)
# S3 method for default
find_parameters(x, flatten = FALSE, verbose = TRUE, ...)
```

## Arguments

- x
A fitted model.

- ...
Currently not used.

- flatten
Logical, if

`TRUE`

, the values are returned as character vector, not as list. Duplicated values are removed.- verbose
Toggle messages and warnings.

## Value

A list of parameter names. For simple models, only one list-element,
`conditional`

, is returned.

## Model components

Possible values for the `component`

argument depend on the model class.
Following are valid options:

`"all"`

: returns all model components, applies to all models, but will only have an effect for models with more than just the conditional model component.`"conditional"`

: only returns the conditional component, i.e. "fixed effects" terms from the model. Will only have an effect for models with more than just the conditional model component.`"smooth_terms"`

: returns smooth terms, only applies to GAMs (or similar models that may contain smooth terms).`"zero_inflated"`

(or`"zi"`

): returns the zero-inflation component.`"dispersion"`

: returns the dispersion model component. This is common for models with zero-inflation or that can model the dispersion parameter.`"instruments"`

: for instrumental-variable or some fixed effects regression, returns the instruments.`"location"`

: returns location parameters such as`conditional`

,`zero_inflated`

,`smooth_terms`

, or`instruments`

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

argument - but no auxiliary parameters).`"distributional"`

(or`"auxiliary"`

): components like`sigma`

,`dispersion`

,`beta`

or`precision`

(and other auxiliary parameters) are returned.