`R/marginal-distributions.R`

`marginal_posterior.Rd`

Creates marginal model-averages posterior distributions for a given parameter based on model-averaged posterior samples and parameter name (and formula with at specification).

```
marginal_posterior(
samples,
parameter,
formula = NULL,
at = NULL,
prior_samples = FALSE,
use_formula = TRUE,
transformation = NULL,
transformation_arguments = NULL,
transformation_settings = FALSE,
n_samples = 10000,
...
)
```

- samples
model-averaged posterior samples created by

`mix_posteriors()`

- parameter
parameter of interest

- formula
model formula (needs to be specified if

`parameter`

was part of a formula)- at
named list with predictor levels of the formula for which marginalization should be performed. If a predictor level is missing,

`0`

is used for continuous predictors, the baseline factor level is used for factors with`contrast = "treatment"`

prior distributions, and the parameter is completely omitted for for factors with`contrast = "meandif"`

,- prior_samples
whether marginal prior distributions should be generated

`contrast = "orthonormal"`

, and`contrast = "independent"`

levels- use_formula
whether the parameter should be evaluated as a part of supplied formula

- transformation
transformation to be applied to the prior distribution. Either a character specifying one of the prepared transformations:

- lin
linear transformation in form of

`a + b*x`

- tanh
also known as Fisher's z transformation

- exp
exponential transformation

, or a list containing the transformation function

`fun`

, inverse transformation function`inv`

, and the Jacobian of the transformation`jac`

. See examples for details.- transformation_arguments
a list with named arguments for the

`transformation`

- transformation_settings
boolean indicating whether the settings the

`x_seq`

or`x_range`

was specified on the transformed support- n_samples
number of samples to be drawn for the model-averaged posterior distribution

- ...
additional arguments

`marginal_posterior`

returns a named list of mixed marginal posterior
distributions (either a vector of matrix).
#'